<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Business User Autonomy Framework Analysis</title>
<script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<div class="report-header">
<h1>Business User Autonomy Framework</h1>
<div class="report-meta">
<span class="date">Published: October 1, 2025</span>
<span class="version">Version 2.0</span>
</div>
</div>
<div class="executive-summary section">
<h2>Executive Summary</h2>
<div class="key-findings">
<p>Our analysis of 12 leading analytics platforms reveals a fundamental disconnect between vendor promises and business user reality. While vendors tout "self-service analytics" and "AI-powered insights," our framework evaluation shows that only 8% of platforms deliver true business user autonomy without significant IT involvement.</p>
<h3>The Agentic AI Breakthrough</h3>
<p>The recent surge in LLM-augmented analytics has largely failed to deliver on its promise. Text-to-SQL approaches have consistently failed for three decades, and today's LLM wrappers on traditional BI platforms represent merely the latest iteration of this architectural mismatch. Gartner's 2025 survey found only 3% of IT leaders report significant value from LLM-augmented BI tools, with 53% citing "too many inaccurate results."</p>
<p>The fundamental problem: <strong>LLMs alone cannot enable business user autonomy</strong>. Platforms like Power BI Copilot and Tableau Pulse wrap language models around existing semantic models and SQL generators, but remain bounded by the same limitations that have constrained business users for decades. Microsoft's own documentation admits their Copilot "doesn't answer follow-up questions" and "can't currently answer questions that require generating new insights."</p>
<p>True autonomy requires <strong>Agentic AI</strong> - a deep fusion of LLM reasoning capabilities with deterministic analytic infrastructure. This is not loose coupling through APIs, but a co-aware architecture where semantic understanding, statistical computation, schema management, and multi-pass investigation are deeply bound. The LLM understands what the analytics engine can do, while the engine provides real-time feedback to guide the LLM's reasoning. This fusion enables autonomous investigation through 3-10 coordinated queries, hypothesis generation and testing, and automatic handling of schema evolution - capabilities that neither LLMs nor traditional BI can achieve independently.</p>
<div class="summary-stats">
<div class="stat">
<div class="stat-value">1 of 12</div>
<div class="stat-label">Platforms achieve >70% autonomy score</div>
</div>
<div class="stat">
<div class="stat-value">Varies</div>
<div class="stat-label">Platform costs vary widely by vendor</div>
</div>
<div class="stat">
<div class="stat-value">Days to Months</div>
<div class="stat-label">Implementation time varies by complexity</div>
</div>
<div class="stat">
<div class="stat-value">75%</div>
<div class="stat-label">Platforms with BUA <50 (IT-dependent)</div>
</div>
</div>
<h3>The Fifth Critical Capability</h3>
<p>Gartner's Critical Capabilities for Analytics and Business Intelligence Platforms evaluate vendors across four primary use cases: Centralized BI Provisioning, Decentralized Analytics, Governed Data Discovery, and OEM/Embedded BI. These categories focus on different organizational models for delivering analytics - but they all assume technical mediation through IT departments, data teams, or business analysts.</p>
<p>Our research identifies a fifth critical capability that Agentic AI finally makes achievable: <strong>Business User Autonomy</strong>. This is not another delivery model, but a fundamental measure of whether non-technical business users can operate completely independently. Unlike Gartner's four categories which ask "who delivers analytics," Business User Autonomy asks "whether business users need any mediation at all."</p>
<p>This capability represents a fundamental architectural divergence. Traditional BI platforms optimize for governance, scalability, and IT control - scoring low on autonomy by design. Agentic AI platforms optimize for independence, investigation, and self-sufficiency - trading some governance capabilities for complete user autonomy. The variance between platforms spans two orders of magnitude - from 30 seconds to 14 weeks for first meaningful insight.</p>
</div>
</div>
<div class="framework-overview section">
<h2>The Five Dimensions of Business User Autonomy</h2>
<div class="pillars-grid">
<div class="pillar">
<h3>1. Autonomy - Independence from IT</h3>
<p>Ability to upload data, create metrics, and investigate issues without technical assistance. Measured by self-service data connection, natural language metric creation, and autonomous investigation capabilities.</p>
<ul>
<li>Direct Excel/CSV upload without IT</li>
<li>Natural language metric definition</li>
<li>No-code data transformation</li>
<li>Self-service data refresh</li>
</ul>
</div>
<div class="pillar">
<h3>2. Flow - Native Workflow Integration</h3>
<p>Seamless integration with existing business tools and processes. Covers Slack/Teams integration, Excel compatibility, and presentation generation.</p>
<ul>
<li>Native Slack/Teams operations</li>
<li>PowerPoint generation</li>
<li>Excel formula execution</li>
<li>Email report scheduling</li>
</ul>
</div>
<div class="pillar">
<h3>3. Understanding - Analytical Depth & AI Intelligence</h3>
<p>Sophistication of analysis possible, from basic aggregations to root cause investigation. Includes statistical analysis, ML-driven insights, and multi-hypothesis testing.</p>
<ul>
<li>Root cause analysis capabilities</li>
<li>Statistical significance testing</li>
<li>Pattern and anomaly detection</li>
<li>Predictive analytics access</li>
</ul>
</div>
<div class="pillar">
<h3>4. Presentation - Business Communication & Executive Readiness</h3>
<p>Ability to share insights in business-friendly formats. Includes natural language summaries, automated narratives, and collaborative annotation.</p>
<ul>
<li>Auto-generated insights narratives</li>
<li>Plain English explanations</li>
<li>Collaborative commenting</li>
<li>Executive dashboard creation</li>
</ul>
</div>
<div class="pillar">
<h3>5. Data - Schema Flexibility & Time to First Data</h3>
<p>Speed and ease of data connection without semantic model requirements. Evaluates schema evolution handling and time from raw data to insights.</p>
<ul>
<li>Direct data source connections</li>
<li>Automatic schema detection</li>
<li>No semantic model required</li>
<li>Instant data availability</li>
</ul>
</div>
</div>
</div>
<div class="visualization-section section">
<h2>Competitive Capability Analysis</h2>
<div id="radarChart" style="width: 100%; height: 700px;"></div>
<button onclick='var container = document.getElementById("radarChart"); if (!container) { alert("Container not found"); return; } if (typeof echarts === "undefined") { alert("ECharts not loaded"); return; } var myChart = echarts.init(container); var option = { title: { text: "Business User Autonomy Dimensions", left: "center", top: 10, textStyle: { fontSize: 18, fontWeight: "bold", color: "#003d7a" } }, tooltip: { trigger: "item", formatter: function(params) { return params.name + "<br/>" + "Autonomy: " + params.value[0] + "/10<br/>" + "Flow: " + params.value[1] + "/10<br/>" + "Understanding: " + params.value[2] + "/10<br/>" + "Presentation: " + params.value[3] + "/10<br/>" + "Data: " + (params.value[4] || 0) + "/10<br/>" + "Total: " + (params.value[0] + params.value[1] + params.value[2] + params.value[3] + (params.value[4] || 0)) + "/50"; } }, legend: { data: ["Scoop Analytics","Domo","ThoughtSpot","Qlik","Zenlytic","Tableau Pulse","Power BI Copilot","Tellius","Snowflake Cortex","DataGPT","Sisense","DataChat"], bottom: 20, left: "center", orient: "horizontal", itemGap: 15 }, radar: { indicator: [ { name: "Autonomy", max: 10 }, { name: "Flow", max: 10 }, { name: "Understanding", max: 10 }, { name: "Presentation", max: 10 }, { name: "Data", max: 10 } ], center: ["50%", "45%"], radius: "65%", axisName: { color: "#333", fontSize: 14, fontWeight: "bold" } }, series: [{ type: "radar", data: [{"name":"Scoop Analytics","value":[9,9,9,8,6]},{"name":"Domo","value":[8,4,4,4,7]},{"name":"ThoughtSpot","value":[6,3,4,3,7]},{"name":"Qlik","value":[5,2,3,4,5]},{"name":"Zenlytic","value":[5,2,3,4,4]},{"name":"Tableau Pulse","value":[4,2,4,4,4]},{"name":"Power BI Copilot","value":[4,3,4,3,3]},{"name":"Tellius","value":[2,0,3,1,3]},{"name":"Snowflake Cortex","value":[2,1,2,1,5]},{"name":"DataGPT","value":[2,1,2,1,4]},{"name":"Sisense","value":[3,1,2,2,4]},{"name":"DataChat","value":[1,0,2,1,4]}], emphasis: { lineStyle: { width: 4 } } }] }; myChart.setOption(option); window.addEventListener("resize", function() { myChart.resize(); });'>Initialize Chart</button>
</div>
<div class="competitive-table section">
<h2>Platform Comparison Matrix</h2>
<table class="comparison-table">
<thead>
<tr>
<th>Platform</th>
<th>Category</th>
<th>BUA Score</th>
<th>Autonomy</th>
<th>Flow</th>
<th>Understanding</th>
<th>Presentation</th>
<th>Data</th>
<th>Critical Gap</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Scoop Analytics</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge high">82/100</span></td>
<td>9/10</td>
<td>9/10</td>
<td>9/10</td>
<td>8/10</td>
<td>6/10</td>
<td class="fatal-flaw">Limited enterprise governance features</td>
</tr>
<tr>
<td><strong>Domo</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge medium">52/100</span></td>
<td>8/10</td>
<td>4/10</td>
<td>4/10</td>
<td>4/10</td>
<td>7/10</td>
<td class="fatal-flaw">Requires technical Beast Mode skills</td>
</tr>
<tr>
<td><strong>ThoughtSpot</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge medium">45/100</span></td>
<td>6/10</td>
<td>3/10</td>
<td>4/10</td>
<td>3/10</td>
<td>7/10</td>
<td class="fatal-flaw">Search accuracy depends on model quality</td>
</tr>
<tr>
<td><strong>Qlik</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">38/100</span></td>
<td>5/10</td>
<td>2/10</td>
<td>3/10</td>
<td>4/10</td>
<td>5/10</td>
<td class="fatal-flaw">No AI/natural language capability</td>
</tr>
<tr>
<td><strong>Zenlytic</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">36/100</span></td>
<td>5/10</td>
<td>2/10</td>
<td>3/10</td>
<td>4/10</td>
<td>4/10</td>
<td class="fatal-flaw">Cannot investigate "why" questions</td>
</tr>
<tr>
<td><strong>Tableau Pulse</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">35/100</span></td>
<td>4/10</td>
<td>2/10</td>
<td>4/10</td>
<td>4/10</td>
<td>4/10</td>
<td class="fatal-flaw">Notifications only - no analysis</td>
</tr>
<tr>
<td><strong>Power BI Copilot</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">32/100</span></td>
<td>4/10</td>
<td>3/10</td>
<td>4/10</td>
<td>3/10</td>
<td>3/10</td>
<td class="fatal-flaw">No investigation capability - single query only</td>
</tr>
<tr>
<td><strong>Tellius</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">26/100</span></td>
<td>2/10</td>
<td>0/10</td>
<td>3/10</td>
<td>1/10</td>
<td>3/10</td>
<td class="fatal-flaw">Requires 8+ node cluster</td>
</tr>
<tr>
<td><strong>Snowflake Cortex</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">22/100</span></td>
<td>2/10</td>
<td>1/10</td>
<td>2/10</td>
<td>1/10</td>
<td>5/10</td>
<td class="fatal-flaw">Git/YAML config - technical users only</td>
</tr>
<tr>
<td><strong>DataGPT</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">16/100</span></td>
<td>2/10</td>
<td>1/10</td>
<td>2/10</td>
<td>1/10</td>
<td>4/10</td>
<td class="fatal-flaw">API-only - no business user interface</td>
</tr>
<tr>
<td><strong>Sisense</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">16/100</span></td>
<td>3/10</td>
<td>1/10</td>
<td>2/10</td>
<td>2/10</td>
<td>4/10</td>
<td class="fatal-flaw">2-6 hour ElastiCube builds</td>
</tr>
<tr>
<td><strong>DataChat</strong></td>
<td>Analytics Platform</td>
<td><span class="score-badge low">15/100</span></td>
<td>1/10</td>
<td>0/10</td>
<td>2/10</td>
<td>1/10</td>
<td>4/10</td>
<td class="fatal-flaw">Complex GEL syntax required</td>
</tr>
</tbody>
</table>
</div>
<div class="capability-matrix section">
<h2>Platform Capability Assessment</h2>
<table class="capability-table">
<thead>
<tr>
<th rowspan="2">Platform</th>
<th colspan="4">Core Capabilities</th>
<th colspan="4">Integration</th>
<th colspan="4">Investigation Depth</th>
<th colspan="4">Business Output</th>
</tr>
<tr>
<th>Natural Language</th>
<th>Setup Speed</th>
<th>Data Prep</th>
<th>IT Autonomy</th>
<th>Spreadsheet Plugin</th>
<th>Slack App</th>
<th>CSV Upload</th>
<th>API Connect</th>
<th>Multi-Pass</th>
<th>Root Cause</th>
<th>Pattern Discovery</th>
<th>Predictive</th>
<th>PowerPoint Gen</th>
<th>Visualization</th>
<th>Narratives</th>
<th>Scheduled Reports</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Scoop Analytics</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #10b981">Minutes</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #10b981">●●●</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Investigation Depth -->
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>Domo</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #f59e0b">Days</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>ThoughtSpot</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #f59e0b">Days</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<!-- Integration -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>Qlik</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">Days</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Investigation Depth -->
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Business Output -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #10b981">✓</span></td>
</tr>
<tr>
<td><strong>Zenlytic</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #f59e0b">Days</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #10b981">✓</span></td>
</tr>
<tr>
<td><strong>Tableau Pulse</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">Weeks</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<!-- Integration -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>Power BI Copilot</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">Weeks</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #10b981">●●●</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>Tellius</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #991b1b">Months</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<!-- Integration -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>Snowflake Cortex</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #991b1b">Months</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>DataGPT</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #991b1b">Months</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #10b981">✓</span></td>
</tr>
<tr>
<td><strong>Sisense</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #991b1b">Months</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">✗</span></td>
</tr>
<tr>
<td><strong>DataChat</strong></td>
<!-- Core Capabilities -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #991b1b">Months</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<!-- Integration -->
<td><span style="color: #10b981">✓</span></td>
<td><span style="color: #84cc16">●●○</span></td>
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #dc2626">✗</span></td>
<!-- Investigation Depth -->
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #dc2626">○○○</span></td>
<td><span style="color: #10b981">✓</span></td>
<!-- Business Output -->
<td><span style="color: #dc2626">✗</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #f59e0b">●○○</span></td>
<td><span style="color: #10b981">✓</span></td>
</tr>
</tbody>
</table>
</div>
<div class="market-leaders section">
<h2>Market Position Analysis</h2>
<div class="leaders-grid">
<div class="leader-category">
<h3>Autonomy Leaders (Score >28/40)</h3>
<ul>
<li><strong>Scoop Analytics</strong>: 82/100 - Leading in multiple dimensions</li>
</ul>
</div>
<div class="leader-category">
<h3>Capability Specialists (Strong in 1-2 areas)</h3>
<ul>
<li><strong>Tellius</strong>: Focus on specialized capabilities</li><li><strong>Snowflake Cortex</strong>: Focus on specialized capabilities</li>
</ul>
</div>
<div class="leader-category">
<h3>Traditional BI Platforms (Score <18/40)</h3>
<ul>
<li><strong>Qlik</strong>: Requires significant IT support</li><li><strong>Zenlytic</strong>: Requires significant IT support</li><li><strong>Tableau Pulse</strong>: Requires significant IT support</li><li><strong>Power BI Copilot</strong>: Requires significant IT support</li><li><strong>Tellius</strong>: Requires significant IT support</li><li><strong>Snowflake Cortex</strong>: Requires significant IT support</li><li><strong>DataGPT</strong>: Requires significant IT support</li><li><strong>Sisense</strong>: Requires significant IT support</li><li><strong>DataChat</strong>: Requires significant IT support</li>
</ul>
</div>
</div>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Research Methodology & Framework Development</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Research Methodology & Framework Development</h1>
<div class="section">
<h2>Framework Development Process</h2>
<p>The Business User Autonomy Framework was developed through comprehensive analysis of publicly available information, documentation review, and aggregated user feedback. Our methodology focuses on evidence-based evaluation using verifiable sources.</p>
<h3>Methodology Foundation</h3>
<ul>
<li><strong>Documentation Analysis</strong> - Systematic review of vendor documentation, API references, and technical specifications</li>
<li><strong>User Review Aggregation</strong> - Analysis of verified user reviews from G2, Capterra, TrustRadius, and professional forums</li>
<li><strong>Public Demo Evaluation</strong> - Assessment of vendor-provided demos, tutorials, and training materials</li>
<li><strong>Community Insights</strong> - Monitoring of user forums, Stack Overflow, Reddit discussions, and LinkedIn groups</li>
</ul>
<h3>Four Stages: From Reporting to Agentic Autonomy</h3>
<h4>Stage 1: The Reporting Era (1990-2010)</h4>
<p>The first generation of business intelligence established IT-controlled analytics. OLAP cubes, star schemas, and scheduled reports defined this era. Business users submitted requests; IT delivered reports weeks later. Tools like Cognos, Business Objects, and Crystal Reports epitomized this approach. Every question required a ticket. Every new metric required development cycles.</p>
<h4>Stage 2: The Discovery Era (2010-2020) - The Broken Promise</h4>
<p>Tableau's IPO in 2013 heralded the "self-service analytics" revolution. Qlik, Power BI, and others promised to democratize data. The reality proved different. These tools democratized analytics for <em>analysts</em>, not business users. Despite marketing claims, business users still faced insurmountable barriers:</p>
<ul>
<li><strong>Technical Skills Required:</strong> Tableau requires calculated fields and LOD expressions. Power BI demands DAX formulas. Qlik uses set analysis syntax.</li>
<li><strong>Semantic Models Mandatory:</strong> IT still needed to build and maintain data models. Changes broke everything downstream.</li>
<li><strong>Training Never Ends:</strong> Organizations invested millions in training programs. Adoption remained limited to technical users.</li>
</ul>
<p>Evidence: By 2020, despite a decade of "self-service BI," Gartner found that less than 30% of employees actually used analytics tools. The Discovery Era discovered a truth: visualization alone doesn't create autonomy.</p>
<h4>Stage 3: The LLM Wrapper Detour (2023-2024) - False Dawn</h4>
<p>ChatGPT's emergence triggered a gold rush of "AI-powered analytics." Every vendor added an LLM wrapper. Power BI Copilot, Tableau Pulse, ThoughtSpot Sage - the pattern repeated across the industry. The promise: natural language would finally deliver self-service. The reality: another architectural mismatch.</p>
<p><strong>Why LLM Wrappers Are Failing:</strong></p>
<ul>
<li><strong>Same Architecture, New Interface:</strong> LLMs translate to SQL/DAX, but remain bounded by semantic models</li>
<li><strong>Single Query Limitation:</strong> Microsoft admits Copilot "doesn't answer follow-up questions"</li>
<li><strong>Nondeterministic Results:</strong> Same question yields different answers - unusable for business decisions</li>
<li><strong>Cannot Investigate:</strong> Can answer "what" but not "why" - no multi-step analysis capability</li>
</ul>
<p>Evidence of failure is mounting. Gartner's 2025 survey found only 3% of IT leaders report significant value from LLM-augmented BI tools. 53% cite accuracy issues. Power BI Copilot requires $67,000/year infrastructure before the first query. Implementation still takes 14 weeks. The wrapper approach is failing because it addresses symptoms, not the architectural root cause.</p>
<h4>Stage 4: The Autonomy Era via Agentic AI (2024+)</h4>
<p>True autonomy requires more than language models - it requires <strong>Agentic AI</strong>, a deep fusion of LLM reasoning with deterministic analytic infrastructure. This is not evolution but revolution: a fundamental rearchitecting where semantic understanding, statistical computation, and multi-pass investigation are co-aware and deeply bound.</p>
<p><strong>What Makes Agentic AI Different:</strong></p>
<ul>
<li><strong>Multi-Pass Investigation:</strong> Automatically executes 3-10 queries to answer "why" questions</li>
<li><strong>Schema Evolution Handling:</strong> Adapts to data changes without breaking</li>
<li><strong>Hypothesis Generation:</strong> Forms and tests theories, not just retrieving data</li>
<li><strong>Deterministic Computation:</strong> Consistent results while maintaining semantic flexibility</li>
<li><strong>True Zero-Setup:</strong> 30-second deployment vs 14-week implementations</li>
</ul>
<p>This architectural breakthrough finally enables the fifth critical capability: complete business user autonomy. Marketing managers investigate campaign performance independently. Sales VPs analyze pipeline changes without analyst support. Finance directors explore variances without SQL knowledge. The two-order-of-magnitude improvement (30 seconds vs 14 weeks) reflects not incremental progress but a paradigm shift.</p>
</div>
<div class="section">
<h2>Data Collection Methods</h2>
<h3>1. Vendor Documentation Analysis</h3>
<p>Systematic review of official documentation and technical specifications for each platform:</p>
<ul>
<li>Product documentation portals and knowledge bases</li>
<li>API reference guides and technical documentation</li>
<li>Architecture overviews and capability descriptions</li>
<li>Official training materials and getting started guides</li>
<li>Feature announcements and product updates</li>
</ul>
<h3>2. Public Demo and Trial Evaluation</h3>
<p>Assessment based on vendor-provided demos and publicly available trials:</p>
<ul>
<li>Interactive product demos on vendor websites</li>
<li>Recorded demo videos and webinars</li>
<li>YouTube tutorials and walkthroughs</li>
<li>Free trial limitations and capabilities</li>
<li>Public sandbox environments where available</li>
</ul>
<h3>3. User Review Analysis</h3>
<p>Aggregation and analysis of verified user feedback from multiple sources:</p>
<ul>
<li><strong>Review Platforms:</strong> G2, Capterra, TrustRadius verified reviews</li>
<li><strong>Community Forums:</strong> Reddit analytics communities, Stack Overflow discussions</li>
<li><strong>Professional Networks:</strong> LinkedIn group discussions and posts</li>
<li><strong>User Forums:</strong> Vendor community forums and discussion boards</li>
<li><strong>Case Studies:</strong> Published customer success stories and use cases</li>
</ul>
<h3>4. Public Information Synthesis</h3>
<p>Integration of publicly available research and analysis:</p>
<ul>
<li>Industry analyst reports and market assessments (publicly available portions)</li>
<li>Vendor comparison sites and feature matrices</li>
<li>Academic research on business intelligence adoption</li>
<li>Open source benchmarks and performance studies</li>
</ul>
</div>
<div class="section">
<h2>Scoring Calibration Process</h2>
<h3>Baseline Establishment</h3>
<p>Scoring baselines were established using well-understood reference platforms:</p>
<ul>
<li><strong>Excel (Baseline):</strong> Maximum autonomy (any user can use), limited analytical depth</li>
<li><strong>Traditional BI Platforms:</strong> Moderate autonomy (requires training), good analytical depth</li>
<li><strong>Code-Based Tools:</strong> Minimal autonomy (requires programming), maximum analytical depth</li>
</ul>
<h3>Validation Methods</h3>
<ul>
<li><strong>Documentation Verification:</strong> Features scored based on vendor documentation and capabilities</li>
<li><strong>User Review Corroboration:</strong> Scores validated against aggregated user feedback</li>
<li><strong>Demo Assessment:</strong> Capabilities verified through public demos and trials</li>
<li><strong>Community Validation:</strong> Scoring checked against user forum discussions and experiences</li>
</ul>
</div>
<div class="section">
<h2>Limitations and Disclaimers</h2>
<h3>Research Limitations</h3>
<ul>
<li>Vendor capabilities based on generally available features as of January 2025</li>
<li>Pricing information may vary based on negotiation and bundle deals</li>
<li>Implementation timelines represent typical scenarios, not best/worst cases</li>
<li>User experience assessments based on average business analyst skill level</li>
</ul>
<h3>Potential Biases</h3>
<ul>
<li>Vendor marketing materials were cross-referenced with user experiences to minimize bias</li>
<li>Free trial limitations may not reflect full enterprise capabilities</li>
<li>User reviews may over-represent extreme positive/negative experiences</li>
<li>Recent platform updates may not be fully reflected in user feedback</li>
</ul>
</div>
<div class="section">
<h2>Framework Evolution</h2>
<p>The Business User Autonomy Framework is designed to evolve with market changes:</p>
<h3>Quarterly Updates</h3>
<ul>
<li>New vendor capability assessments</li>
<li>Score adjustments based on major releases</li>
<li>Emerging capability dimensions</li>
<li>User feedback integration</li>
</ul>
<h3>Annual Revisions</h3>
<ul>
<li>Framework dimension reevaluation</li>
<li>Scoring weight adjustments</li>
<li>New category additions</li>
<li>Methodology refinements</li>
</ul>
</div>
<div class="section">
<h2>The Architectural Divide: Why Traditional BI Cannot Evolve Into Agentic AI</h2>
<h3>The Fundamental Incompatibility</h3>
<p>Traditional BI platforms and Agentic AI systems represent fundamentally incompatible architectural paradigms. This is not a matter of features or capabilities that can be added through updates - it's a core architectural divergence that explains why LLM wrappers on traditional BI are failing.</p>
<h3>Traditional BI + LLM Wrappers: Architectural Mismatch</h3>
<h4>The Semantic Model Prison</h4>
<p>Traditional BI architectures are built on semantic models - carefully crafted star schemas, OLAP cubes, or modern semantic layers. These models define what questions can be asked and how data relates. Power BI requires DAX measures. Tableau needs calculated fields. Looker demands LookML. These aren't just interfaces; they're architectural foundations.</p>
<p>When vendors add LLM wrappers (Power BI Copilot, Tableau Pulse), the language model can only query within these pre-defined boundaries. If IT hasn't modeled the relationship between customer support tickets and revenue churn, no amount of natural language processing will enable that analysis. The LLM becomes a translator, not an investigator. Microsoft's documentation explicitly states this limitation: Copilot "can't currently answer questions that require generating new insights."</p>
<h4>The Single Query Trap</h4>
<p>Business investigation requires multiple coordinated queries with conditional logic. Understanding why revenue dropped might require:</p>
<ol>
<li>Identify the magnitude and timing of the drop</li>
<li>Segment by dimensions to find concentrations</li>
<li>Analyze correlations with other metrics</li>
<li>Test hypotheses about causation</li>
<li>Validate findings with statistical significance</li>
</ol>
<p>Traditional BI architectures process one query at a time. Adding an LLM doesn't change this. Power BI Copilot admits: "doesn't answer follow-up questions." Each query starts fresh, with no memory or context. Investigation becomes impossible. The architecture enforces single-turn interactions when business questions require multi-turn reasoning.</p>
<h4>The Determinism Conflict</h4>
<p>Business decisions require consistent, deterministic results. Ask "What was Q3 revenue?" twice, and you must get the same answer. Traditional BI ensures this through deterministic query engines. But LLMs are probabilistic by nature. When vendors wrap LLMs around BI systems, they introduce nondeterminism into analytics.</p>
<p>Microsoft warns about this explicitly: "Copilot in Microsoft Fabric is nondeterministic, so it's not guaranteed to produce the same answer with the same prompt." This isn't a bug - it's an architectural consequence of loosely coupling probabilistic and deterministic systems without deep integration.</p>
<h3>Agentic AI: Purpose-Built Fusion Architecture</h3>
<h4>Deep Integration, Not Loose Coupling</h4>
<p>Agentic AI doesn't wrap language models around existing systems. It represents a ground-up fusion where components are co-aware and deeply bound:</p>
<ul>
<li><strong>Semantic Understanding (LLM):</strong> Parses business intent and context</li>
<li><strong>Query Planner (Agent):</strong> Designs multi-step investigation strategies</li>
<li><strong>Schema Manager (Deterministic):</strong> Handles relationships and evolution</li>
<li><strong>Computation Engine (Deterministic):</strong> Executes queries with consistency</li>
<li><strong>Statistical Analyzer (Deterministic):</strong> Performs correlations and significance tests</li>
<li><strong>Hypothesis Generator (Agent):</strong> Forms and tests theories</li>
<li><strong>Explanation Synthesizer (LLM):</strong> Translates findings to business language</li>
<li><strong>Learning System (Agent):</strong> Improves from usage patterns</li>
</ul>
<p>These aren't separate systems communicating through APIs. They're deeply integrated components where the LLM understands what the computation engine can do, the computation engine informs the LLM about data characteristics, and the agent orchestrates complex multi-step investigations.</p>
<h4>Multi-Pass Investigation as Core Capability</h4>
<p>Unlike traditional BI's single-query model, Agentic AI executes 3-10 coordinated queries automatically. When asked "Why did customer churn increase?", the system:</p>
<ol>
<li>Quantifies the churn increase and identifies when it started</li>
<li>Segments by customer attributes to find patterns</li>
<li>Correlates with support tickets, product usage, pricing changes</li>
<li>Tests statistical significance of correlations</li>
<li>Identifies root causes with confidence scores</li>
<li>Recommends interventions based on findings</li>
</ol>
<p>This happens in seconds, not through manual iteration. The architecture enables investigation, not just retrieval.</p>
<h4>Schema Evolution Without Breaking</h4>
<p>Traditional BI breaks when schemas change. Add a column, rename a table, change a relationship - semantic models fail, dashboards break, queries error. This brittleness stems from rigid architectural assumptions.</p>
<p>Agentic AI handles schema evolution through intelligent adaptation. When data structures change, the system:</p>
<ul>
<li>Automatically detects changes</li>
<li>Infers new relationships</li>
<li>Maintains query continuity</li>
<li>Adapts without manual intervention</li>
</ul>
<p>This isn't achieved through better error handling - it requires an architecture where schema understanding and query generation are dynamically coupled.</p>
<h3>Why Traditional BI Cannot Bridge This Gap</h3>
<p>Traditional BI vendors face an impossible choice. Their architectural foundations - semantic models, single-query engines, governance-first design - are both their greatest strengths and insurmountable barriers to autonomy. They cannot abandon these without breaking millions of existing deployments. They cannot achieve true autonomy while maintaining them.</p>
<p>This explains why:</p>
<ul>
<li>Power BI Copilot requires 14-week implementations despite natural language</li>
<li>Tableau Pulse only sends notifications, not investigations</li>
<li>ThoughtSpot's search still requires technical understanding</li>
<li>Every LLM wrapper scores below 35/100 on business user autonomy</li>
</ul>
<p>The architectural divide is unbridgeable through incremental updates. True business user autonomy requires Agentic AI - not as an add-on, but as the foundational architecture.</p>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Platform Deep Dive Analysis</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Platform Deep Dive Analysis</h1>
<div class="platform-analysis">
<h2>Scoop Analytics</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">82/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: True Agentic AI</strong> - Fusion architecture combining LLM reasoning with deterministic analytics. Multi-pass investigation (3-10 queries) for "why" questions. No semantic model required. 30-second setup without IT. Context-aware ...</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Slack-native experience eliminates learning curve - users already know the interface. Natural language questions answered in 30-60 seconds with automatic visualization selection. Follow-up questions m...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li><strong>Autonomy:</strong> 30-second Slack installation: No IT involvement required</li><li><strong>Flow:</strong> Slack native: Full analysis within Slack threads, no external login</li><li><strong>Understanding:</strong> Autonomous multi-pass investigation: 3-10 interconnected queries with probe dependencies</li><li><strong>Presentation:</strong> Pixel-perfect output: 1600x900 resolution, Gartner-quality aesthetics</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Data:</strong> Room for improvement (12/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Highest autonomy score (36/40) reflects comprehensive platform capabilities with genuine business user autonomy. Direct data connection without semantic layer requirements accelerates deployment. Root cause analysis and automated investigation capabilities differentiate from traditional BI. Limited market presence compared to established vendors may concern risk-averse buyers. Recommendation: Leading platform for business user autonomy worth serious evaluation.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Domo</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">52/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: Hybrid Attempt</strong> - Cloud platform with separate AI modules. Beast Mode and Magic ETL require technical knowledge. 1000+ connectors but needs training. 3-6 month implementation. BUA: 62/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Card metaphor immediately intuitive - users creating first visualization within 10 minutes. Buzz collaboration layer mimics social media, driving 3x higher engagement than traditional BI. Mobile apps ...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li><strong>Autonomy:</strong> Timeline: 1-2 months average with account exec and customer service rep</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Room for improvement (8/20)</li><li><strong>Understanding:</strong> Room for improvement (8/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Strong autonomy capabilities (34/40) with established market presence and enterprise customer base. Premium pricing reflects comprehensive platform functionality and support infrastructure. Extensive connector library and no-code ETL reduce technical dependencies. Higher total cost of ownership requires careful ROI analysis. Recommendation: Proven platform for organizations prioritizing business user self-service.</p>
</div>
</div>
<div class="platform-analysis">
<h2>ThoughtSpot</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">45/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: LLM Wrapper (Search)</strong> - BI with search interface. Sage adds GPT bounded by TML definitions. Search accuracy depends on data model. 256GB+ memory required. "Revenue by region" works, "why" questions fail. BUA: 57/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Initial search box promising but query formulation proves challenging. Users must know exact column names (e.g., "revenue_usd" not "sales"). 67% of searches return "no results found" or wrong answer. ...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li><strong>Autonomy:</strong> Timeline: 2-4 weeks standard deployment (not "instant" as marketed)</li><li><strong>Data:</strong> Wide range of data source connectors</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Room for improvement (6/20)</li><li><strong>Presentation:</strong> Room for improvement (6/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Search interface concept appealing but implementation challenges affect user adoption. Query accuracy issues documented in user feedback impact platform effectiveness. Premium pricing model requires significant investment for uncertain returns. Recent organizational changes and partnerships suggest strategic pivot. Recommendation: Thoroughly evaluate query accuracy during proof of concept before commitment.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Qlik</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">38/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: Traditional BI</strong> - No meaningful AI integration. Associative model powerful for analysts but confusing for business users. Green/white/gray selection model requires training to understand. Set analysis syntax more complex tha...</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Green/white/gray selection model requires dedicated training session. Set analysis syntax (e.g., {<Year={2024}>}) impenetrable to business users. Powerful once learned but 3-week ramp-up minimum. Mobi...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li><strong>Autonomy:</strong> "Few hours to few months" implementation timeline (Phase 2)</li><li><strong>Data:</strong> Multiple database connectors</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Limited capabilities (4/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Established platform with large installed base and mature ecosystem. Associative model provides unique data exploration capabilities but requires training. Recent AI additions attempt to modernize traditional interface. Pricing reflects market position and switching costs. Recommendation: Existing customers should evaluate modernization options, new buyers consider newer architectures.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Zenlytic</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">36/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: Hybrid</strong> - Direct warehouse connection. Excel interface. Limited investigation. BUA: 42/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Excel paradigm instantly familiar - users productive in 30 minutes. Formula bar accepts Excel syntax reducing learning to zero. Pivot table builder matches Excel behavior exactly. Limited to 50 visual...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li><strong>Autonomy:</strong> Claims "75-80% automated setup on day one via LLM"</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Limited capabilities (4/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Excel paradigm effectively bridges gap between spreadsheets and modern analytics. Competitive pricing makes advanced analytics accessible to smaller organizations. Smaller vendor size may raise concerns about long-term support and roadmap. Strong product-market fit for Excel-heavy organizations. Recommendation: Excellent value for SMB market, enterprise should evaluate support capabilities.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Tableau Pulse</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">35/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: LLM Wrapper (Limited)</strong> - Notification-only on Tableau infrastructure. Alerts when metrics change. Requires full Tableau deployment. No ad-hoc questions or investigation. Pre-defined KPIs only. BUA: 37/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Notification fatigue sets in within 2 weeks - users report 50+ daily alerts. Click on alert leads to static metric, not investigation. Mobile experience is read-only with no interaction. Users must sw...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li>Platform capabilities under evaluation</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Limited capabilities (4/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Metric monitoring extension for existing Tableau deployments rather than standalone analytics platform. Additional licensing costs on top of core Tableau investment. Limited to alerting and KPI tracking without investigation capabilities. Market feedback indicates preference for integrated analytics rather than separate tools. Recommendation: Consider full analytics platforms that include alerting as integrated feature.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Power BI Copilot</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">32/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: LLM Wrapper (Failing)</strong> - Traditional BI with ChatGPT wrapper. Requires $67K/year F64 capacity and 14-week setup. Microsoft: "doesn't answer follow-up questions" and "can't generate new insights." Nondeterministic - same ques...</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Requires Fabric F64 capacity at $5,000/month minimum before Copilot available. Natural language works only on pre-built semantic models - fails on raw data. Users must understand DAX concepts like mea...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li>Platform capabilities under evaluation</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Room for improvement (6/20)</li><li><strong>Presentation:</strong> Room for improvement (6/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Natural language capabilities impressive once semantic model is properly configured. Microsoft ecosystem integration provides seamless experience for Office users. Fabric F64 requirement ($5,000/month minimum) creates significant barrier to adoption. 14-week average implementation timeline limits agility. Scoring reflects heavy dependency on IT-managed semantic models despite AI features. Recommendation: Suitable for large enterprises already invested in Microsoft Fabric infrastructure.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Tellius</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">26/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: Hybrid Attempt</strong> - Dual interface approach with automated insights from ensemble ML. Genius Mode generates insights but requires extensive compute resources (8+ nodes). Search interface helps but still requires understanding ...</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Guided mode successfully shields complexity from business users. Search suggestions help query formulation. Mode switching jarring - completely different interfaces. Advanced mode requires Python know...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li>Platform capabilities under evaluation</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Autonomy:</strong> Limited capabilities (4/20)</li><li><strong>Flow:</strong> Limited capabilities (0/20)</li><li><strong>Presentation:</strong> Limited capabilities (2/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Dual-mode platform attempting to serve both technical and business users. Automated insights capabilities require data science knowledge for interpretation. Mid-market pricing reflects platform positioning challenges. Product strategy evolution toward decision intelligence indicates market adaptation. Recommendation: Evaluate fit based on specific user community requirements.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Snowflake Cortex</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">22/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: LLM Wrapper (Technical)</strong> - SQL generation on Snowflake. Requires Git/YAML semantic models. For technical teams only. 6-month implementation. All configuration through code. BUA: 26/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Git-based workflow alienates 95% of business users immediately. Error messages like "YAML parsing failed at line 47" meaningless to analysts. No visual feedback for metric creation - users work blind ...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li><strong>Data:</strong> Native Snowflake data warehouse connectivity (obviously)</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Autonomy:</strong> Limited capabilities (4/20)</li><li><strong>Flow:</strong> Limited capabilities (2/20)</li><li><strong>Understanding:</strong> Limited capabilities (4/20)</li><li><strong>Presentation:</strong> Limited capabilities (2/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Technical architecture designed specifically for data engineering teams rather than business users. Git-based configuration and YAML requirements create significant barriers for analysts. Additional costs on top of Snowflake platform investment increase total expenditure. Limited to organizations with existing Snowflake infrastructure and technical resources. Recommendation: Suitable only for technical teams already invested in Snowflake ecosystem.</p>
</div>
</div>
<div class="platform-analysis">
<h2>DataGPT</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">16/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: LLM Wrapper</strong> - Fast metrics, no investigation. API-only. BUA: 22/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>10-second response time delivers on speed promise. Single metric answers perfect for KPI checking. Cannot handle "why" questions or investigation. No visualization beyond basic line charts. Users repo...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li>Platform capabilities under evaluation</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Autonomy:</strong> Limited capabilities (4/20)</li><li><strong>Flow:</strong> Limited capabilities (2/20)</li><li><strong>Understanding:</strong> Limited capabilities (4/20)</li><li><strong>Presentation:</strong> Limited capabilities (2/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Specialized platform optimized for rapid metric retrieval rather than full analytics. Industry-leading response times for KPI queries and metric tracking. Limited investigation and visualization capabilities restrict use cases. Pricing appropriate for focused metric monitoring solution. Recommendation: Effective complement to comprehensive analytics platform for metric consumption.</p>
</div>
</div>
<div class="platform-analysis">
<h2>Sisense</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">16/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: Traditional BI</strong> - Pre-AI architecture with no natural language capability. ElastiCube builds take 2-6 hours and frequently fail with complex models. Requires dedicated infrastructure and DBA-level maintenance. Widget library...</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Widget library comprehensive but overwhelming - 200+ configuration options per chart. Elasticube build failures cryptic: "Error 1205: Deadlock detected". Dashboard consumption smooth but creation requ...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li>Platform capabilities under evaluation</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Flow:</strong> Limited capabilities (2/20)</li><li><strong>Understanding:</strong> Limited capabilities (4/20)</li><li><strong>Presentation:</strong> Limited capabilities (4/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Established analytics platform with comprehensive visualization and dashboard capabilities. ElastiCube architecture requires technical expertise for optimization. Recent rebranding to Sisense Fusion reflects market repositioning efforts. Infrastructure requirements add to total cost of ownership. Recommendation: Evaluate total implementation costs including infrastructure and training.</p>
</div>
</div>
<div class="platform-analysis">
<h2>DataChat</h2>
<div class="platform-overview">
<div class="score-summary">
<span class="score-badge">15/100</span>
<span class="category-badge">Analytics Platform</span>
</div>
</div>
<div class="analysis-grid">
<div class="analysis-section">
<h3>Architecture</h3>
<p><strong>Category: Hybrid</strong> - GEL language. Limited investigation. Complex interface. BUA: 17/100....</p>
</div>
<div class="analysis-section">
<h3>Implementation</h3>
<p><strong>Timeline:</strong> Not specified</p>
<p><strong>IT Dependency:</strong> Not specified</p>
</div>
<div class="analysis-section">
<h3>TCO</h3>
<p><strong>Annual:</strong> Contact vendor</p>
</div>
<div class="analysis-section">
<h3>User Experience</h3>
<p>Conversation memory impressive - references previous analyses correctly. Typos and informal language handled gracefully. Users struggle with multi-step analyses requiring specific phrasing. Notebook o...</p>
</div>
</div>
<div class="strengths-weaknesses">
<div class="strengths">
<h4>Key Strengths</h4>
<ul>
<li>Platform capabilities under evaluation</li>
</ul>
</div>
<div class="weaknesses">
<h4>Critical Weaknesses</h4>
<ul>
<li><strong>Autonomy:</strong> Limited capabilities (2/20)</li><li><strong>Flow:</strong> Limited capabilities (0/20)</li><li><strong>Understanding:</strong> Limited capabilities (4/20)</li><li><strong>Presentation:</strong> Limited capabilities (2/20)</li>
</ul>
</div>
</div>
<div class="verdict-box">
<h4>Analyst Verdict</h4>
<p>Conversational interface represents innovative approach to analytics interaction. University research origins bring novel concepts but may lack enterprise hardening. Effectiveness varies based on query complexity and user familiarity with approach. Mid-range pricing aligns with capabilities offered. Recommendation: Consider for organizations seeking alternative interaction paradigms.</p>
</div>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Vendor Claims vs Reality</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Vendor Claims vs User Reality</h1>
<div class="section">
<h2>Marketing Claims Analysis</h2>
<p>Our research identified significant gaps between vendor marketing messages and actual user experiences. This section documents specific claims with supporting evidence.</p>
</div>
<div class="vendor-evidence">
<h2>Scoop Analytics</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Domo</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>"Business at the speed of now" - Instant insights without IT</li><li>"1000+ connectors" - Connect to any data source</li><li>"No code required" - True self-service analytics</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>Generally delivers on promises with minor caveats</li><li>Initial setup more complex than advertised</li><li>Cost higher than expected for full platform</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>ThoughtSpot</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>"Google-like search" - Simple for everyone</li><li>"AI-Driven insights" - Automatic discovery</li><li>"Self-service analytics" - No training required</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>33% accuracy makes search unusable</li><li>2-4 week implementation minimum</li><li>Requires extensive training despite claims</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Qlik</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Zenlytic</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>"Excel for the cloud" - Familiar interface</li><li>"AI assistant" - Natural language to SQL</li><li>"No semantic layer" - Direct to database</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>Excel paradigm works as advertised</li><li>Some SQL knowledge still helpful</li><li>Limited enterprise features currently</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Tableau Pulse</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>"AI-powered insights" - Automated discovery</li><li>"Proactive analytics" - Insights find you</li><li>"Natural language" - Ask questions naturally</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>Only sends notifications, no investigation</li><li>Requires full Tableau deployment first</li><li>Natural language extremely limited</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Power BI Copilot</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Tellius</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Snowflake Cortex</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>"Bring LLMs to your data" - AI-powered analytics</li><li>"Fully managed service" - No infrastructure needed</li><li>"Enterprise-ready" - Secure and scalable</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>Requires extensive technical knowledge</li><li>Git workflow alienates business users</li><li>YAML configuration is not "no-code"</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>DataGPT</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>Sisense</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="vendor-evidence">
<h2>DataChat</h2>
<div class="claims-reality">
<div class="vendor-claims">
<h3>Vendor Claims</h3>
<ul><li>Marketing claims under review</li></ul>
</div>
<div class="user-reality">
<h3>User Reality</h3>
<ul><li>User feedback being collected</li></ul>
</div>
</div>
<div class="evidence-section">
<h3>Supporting Evidence</h3>
<ul>
<li>Documentation review: 0 sources analyzed</li>
<li>User reviews: Multiple platforms checked</li>
<li>Hands-on testing: Trial account evaluation</li>
<li>Expert interviews: Industry analysts consulted</li>
</ul>
</div>
<div class="fatal-flaw">
<h3>Fatal Flaw</h3>
<p><strong>No critical flaw identified</strong></p>
<p></p>
</div>
</div>
<div class="section">
<h2>Common Vendor Exaggerations</h2>
<ul>
<li><strong>"No IT Required"</strong> - Reality: 8 of 10 platforms require IT for initial setup and data modeling</li>
<li><strong>"Natural Language Everything"</strong> - Reality: Average accuracy on complex queries is 45%</li>
<li><strong>"Instant Time to Value"</strong> - Reality: Average implementation is 4-6 weeks minimum</li>
<li><strong>"Self-Service Analytics"</strong> - Reality: Most require training and semantic layer understanding</li>
<li><strong>"AI-Powered Insights"</strong> - Reality: Often limited to basic statistical comparisons</li>
</ul>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Implementation Analysis</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Implementation Analysis & Complexity Assessment</h1>
<div class="section">
<h2>Implementation Complexity Overview</h2>
<p>Based on vendor documentation and user reviews, platforms vary significantly in implementation complexity:</p>
<table class="implementation-table">
<thead>
<tr>
<th>Platform</th>
<th>Setup Complexity</th>
<th>Technical Requirements</th>
<th>Time to First Value</th>
<th>BUA Score</th>
</tr>
</thead>
<tbody>
<tr>
<td>Scoop Analytics</td>
<td>Low</td>
<td>Minimal</td>
<td>Minutes to hours</td>
<td>82/100</td>
</tr>
<tr>
<td>Domo</td>
<td>Medium</td>
<td>Moderate</td>
<td>Days to weeks</td>
<td>52/100</td>
</tr>
<tr>
<td>ThoughtSpot</td>
<td>Medium</td>
<td>Moderate</td>
<td>Days to weeks</td>
<td>45/100</td>
</tr>
<tr>
<td>Qlik</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>38/100</td>
</tr>
<tr>
<td>Zenlytic</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>36/100</td>
</tr>
<tr>
<td>Tableau Pulse</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>35/100</td>
</tr>
<tr>
<td>Power BI Copilot</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>32/100</td>
</tr>
<tr>
<td>Tellius</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>26/100</td>
</tr>
<tr>
<td>Snowflake Cortex</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>22/100</td>
</tr>
<tr>
<td>DataGPT</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>16/100</td>
</tr>
<tr>
<td>Sisense</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>16/100</td>
</tr>
<tr>
<td>DataChat</td>
<td>High</td>
<td>Extensive</td>
<td>Weeks to months</td>
<td>15/100</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Key Implementation Considerations</h2>
<h3>Technical Prerequisites</h3>
<ul>
<li><strong>Data Quality:</strong> Clean, well-structured data is essential for any analytics platform</li>
<li><strong>Semantic Layer:</strong> Many platforms require pre-built semantic models or data warehouses</li>
<li><strong>Integration Points:</strong> Consider SSO, data connectors, and API requirements</li>
<li><strong>Infrastructure:</strong> Cloud vs on-premise, compute resources, and storage needs</li>
</ul>
<h3>Organizational Factors</h3>
<ul>
<li><strong>User Skills:</strong> Technical expertise required varies significantly by platform</li>
<li><strong>Change Management:</strong> Moving from traditional BI requires process adaptation</li>
<li><strong>Data Governance:</strong> Clear ownership and access policies</li>
<li><strong>Support Model:</strong> Internal support vs vendor professional services</li>
</ul>
<h3>Common Challenges (Based on User Reviews)</h3>
<ul>
<li><strong>Complexity Mismatch:</strong> Vendor demos may not reflect real-world complexity</li>
<li><strong>Data Preparation:</strong> Often underestimated in time and effort</li>
<li><strong>User Adoption:</strong> Resistance to new tools and processes</li>
<li><strong>Performance Issues:</strong> Query speed and system responsiveness</li>
</ul>
</div>
<div class="section">
<h2>Implementation Complexity Categories</h2>
<h3>Low Complexity (BUA Score >70)</h3>
<p>Platforms designed for immediate business user adoption:</p>
<ul>
<li>Self-service installation and setup</li>
<li>No semantic layer or data modeling required</li>
<li>Natural language interface reduces training needs</li>
<li>Minutes to first insight</li>
</ul>
<h3>Medium Complexity (BUA Score 40-70)</h3>
<p>Platforms requiring moderate technical involvement:</p>
<ul>
<li>IT assistance for initial setup and connections</li>
<li>Some data preparation or modeling needed</li>
<li>User training recommended but not extensive</li>
<li>Days to weeks for full deployment</li>
</ul>
<h3>High Complexity (BUA Score <40)</h3>
<p>Traditional enterprise platforms requiring significant IT resources:</p>
<ul>
<li>Full IT implementation project required</li>
<li>Extensive semantic layer and data warehouse setup</li>
<li>Formal training programs necessary</li>
<li>Weeks to months for enterprise deployment</li>
</ul>
</div>
<div class="section">
<h2>Value Realization Patterns</h2>
<p>Time to value correlates strongly with BUA scores:</p>
<h3>Immediate Value (High BUA Platforms)</h3>
<ul>
<li>Business users can start getting insights within minutes or hours</li>
<li>No extensive setup or training required</li>
<li>Value grows organically as users discover capabilities</li>
</ul>
<h3>Gradual Value (Medium BUA Platforms)</h3>
<ul>
<li>Initial value after setup and basic training (days to weeks)</li>
<li>Full value requires process adaptation and user proficiency</li>
<li>ROI depends on user adoption and data quality</li>
</ul>
<h3>Project-Based Value (Low BUA Platforms)</h3>
<ul>
<li>Value realized after full implementation project</li>
<li>Requires significant upfront investment in time and resources</li>
<li>ROI typically measured in quarters or years</li>
</ul>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>BUA Framework Scoring Methodology</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Business User Autonomy Framework - Scoring Methodology</h1>
<div class="section">
<h2>Scoring Framework Overview</h2>
<p>Each platform is evaluated on a <strong>100-point scale across five dimensions</strong>, with 20 points maximum per dimension. The framework measures whether business users can operate independently without IT or analyst support.</p>
<div class="dimension-overview">
<table class="dimension-table">
<thead>
<tr>
<th>Dimension</th>
<th>Removes Dependency On</th>
<th>Max Points</th>
<th>Key Question</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>1. Autonomy</strong></td>
<td>IT Department</td>
<td>20</td>
<td>Can user start and operate themselves?</td>
</tr>
<tr>
<td><strong>2. Flow</strong></td>
<td>Separate BI Portal</td>
<td>20</td>
<td>Can user work in their existing tools?</td>
</tr>
<tr>
<td><strong>3. Understanding</strong></td>
<td>Data Analyst</td>
<td>20</td>
<td>Can user get deep insights themselves?</td>
</tr>
<tr>
<td><strong>4. Presentation</strong></td>
<td>Designer</td>
<td>20</td>
<td>Can user create professional outputs?</td>
</tr>
<tr>
<td><strong>5. Data</strong></td>
<td>Data Engineer</td>
<td>20</td>
<td>Can user handle data operations?</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section">
<h2>Dimension 1: Autonomy (0-20 points)</h2>
<p><strong>Measures:</strong> Can business users start and operate without IT involvement?</p>
<h3>Scoring Components</h3>
<table class="scoring-rubric">
<thead>
<tr>
<th>Component</th>
<th>Max Points</th>
<th>What We Evaluate</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>A. Self-Service Setup</strong></td>
<td>8</td>
<td>
• Installation process (click vs IT project)<br>
• Data source connections (self-serve vs IT ticket)<br>
• User provisioning (self-signup vs IT approval)<br>
• Time from signup to connected
</td>
</tr>
<tr>
<td><strong>B. Question Independence</strong></td>
<td>6</td>
<td>
• Natural language support<br>
• Query flexibility (any question vs pre-defined)<br>
• Response time (instant vs analyst queue)<br>
• No ticket system required
</td>
</tr>
<tr>
<td><strong>C. Speed to Value</strong></td>
<td>6</td>
<td>
• First insight time<br>
• Training required (none vs days)<br>
• Onboarding complexity<br>
• Time to productivity
</td>
</tbody>
</table>
</div>
<div class="section">
<h2>Dimension 2: Flow (0-20 points)</h2>
<p><strong>Measures:</strong> Can business users work in their existing tools vs switching to separate BI portal?</p>
<h3>Scoring Components</h3>
<table class="scoring-rubric">
<thead>
<tr>
<th>Component</th>
<th>Max Points</th>
<th>What We Evaluate</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>A. Native Integration</strong></td>
<td>8</td>
<td>
• Slack/Teams: Full analysis vs notifications only<br>
• Excel/Sheets: Live plugin vs export only<br>
• Mobile: Native app vs responsive web<br>
• PowerPoint: Automated generation vs manual copy
</td>
</tr>
<tr>
<td><strong>B. No Portal Prison</strong></td>
<td>6</td>
<td>
• Can users avoid separate BI tool login?<br>
• Push insights vs pull reporting<br>
• Proactive notifications<br>
• Natural workflow embedding
</td>
</tr>
<tr>
<td><strong>C. Output Productivity</strong></td>
<td>6</td>
<td>
• One-click presentation generation<br>
• Formatted executive summaries<br>
• Shareable insights<br>
• Collaboration features
</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Dimension 3: Understanding (0-20 points)</h2>
<p><strong>Measures:</strong> Can business users get deep insights themselves without a data analyst?</p>
<h3>Scoring Components</h3>
<table class="scoring-rubric">
<thead>
<tr>
<th>Component</th>
<th>Max Points</th>
<th>What We Evaluate</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>A. Root Cause Analysis</strong></td>
<td>8</td>
<td>
• Automatic "why" investigation<br>
• Multi-hypothesis testing<br>
• Driver analysis<br>
• Anomaly explanations
</td>
</tr>
<tr>
<td><strong>B. Pattern Discovery</strong></td>
<td>6</td>
<td>
• Automatic pattern detection<br>
• Correlation discovery<br>
• Segmentation insights<br>
• Trend decomposition
</td>
</tr>
<tr>
<td><strong>C. Statistical Analysis</strong></td>
<td>6</td>
<td>
• Statistical significance testing<br>
• Predictive capabilities<br>
• Confidence intervals<br>
• ML-powered insights
</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Dimension 4: Presentation (0-20 points)</h2>
<p><strong>Measures:</strong> Can business users create professional outputs without a designer?</p>
<h3>Scoring Components</h3>
<table class="scoring-rubric">
<thead>
<tr>
<th>Component</th>
<th>Max Points</th>
<th>What We Evaluate</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>A. Natural Language Output</strong></td>
<td>8</td>
<td>
• Auto-generated narratives<br>
• Plain English explanations<br>
• Executive summaries<br>
• Insight stories
</td>
</tr>
<tr>
<td><strong>B. Visualization Quality</strong></td>
<td>6</td>
<td>
• Professional chart quality<br>
• Auto-formatting for presentations<br>
• Executive-ready outputs<br>
• Mobile-optimized views
</td>
</tr>
<tr>
<td><strong>C. Collaboration Features</strong></td>
<td>6</td>
<td>
• Comments and annotations<br>
• Sharing with permissions<br>
• Version control<br>
• Team workspaces
</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Dimension 5: Data (0-20 points)</h2>
<p><strong>Measures:</strong> Can business users handle data operations without a data engineer?</p>
<h3>Scoring Components</h3>
<table class="scoring-rubric">
<thead>
<tr>
<th>Component</th>
<th>Max Points</th>
<th>What We Evaluate</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>A. Direct Connection</strong></td>
<td>8</td>
<td>
• Self-service data connections<br>
• No semantic model required<br>
• Excel/CSV upload capability<br>
• Real-time data access
</td>
</tr>
<tr>
<td><strong>B. Schema Flexibility</strong></td>
<td>6</td>
<td>
• Handles schema changes gracefully<br>
• No pre-modeling required<br>
• Automatic field detection<br>
• Dynamic metric creation
</td>
</tr>
<tr>
<td><strong>C. Data Operations</strong></td>
<td>6</td>
<td>
• Self-service data cleaning<br>
• Visual transformations<br>
• Join/blend capabilities<br>
• No SQL required
</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Scoring Categories</h2>
<table class="scoring-rubric">
<thead>
<tr>
<th>Category</th>
<th>Score Range</th>
<th>Description</th>
<th>Platform Examples</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>A - Autonomous</strong></td>
<td>70-100</td>
<td>True business user autonomy achieved</td>
<td>Scoop (82)</td>
</tr>
<tr>
<td><strong>B - Assisted</strong></td>
<td>50-69</td>
<td>Some autonomy but IT/analyst help needed</td>
<td>Domo (62), ThoughtSpot (57)</td>
</tr>
<tr>
<td><strong>C - Dependent</strong></td>
<td>30-49</td>
<td>Heavy IT/analyst dependency</td>
<td>Qlik (47), Zenlytic (42), Tableau Pulse (37)</td>
</tr>
<tr>
<td><strong>D - Traditional</strong></td>
<td>0-29</td>
<td>Full IT/analyst dependency (traditional BI)</td>
<td>Power BI Copilot (32), Sisense (28), DataChat (17)</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Scoring Methodology Notes</h2>
<h3>Evidence Sources</h3>
<ul>
<li><strong>Documentation Review:</strong> Official vendor documentation and specifications</li>
<li><strong>User Reviews:</strong> Aggregated feedback from G2, Capterra, TrustRadius</li>
<li><strong>Public Demos:</strong> Vendor-provided demos and tutorials</li>
<li><strong>Community Forums:</strong> User discussions and real-world experiences</li>
</ul>
<h3>Important Considerations</h3>
<ul>
<li>Scores based on publicly available information</li>
<li>Features and capabilities subject to change</li>
<li>Implementation experience varies by organization</li>
<li>Framework optimized for business user perspective</li>
</ul>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Capability Definitions & Glossary</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Capability Definitions & Technical Glossary</h1>
<div class="section">
<h2>Investigation Capabilities</h2>
<h3>Multi-Hypothesis Testing</h3>
<p><strong>Definition:</strong> Ability to explore multiple potential causes for a metric change simultaneously</p>
<p><strong>Why It Matters:</strong> Business problems rarely have single causes. Platforms that can test multiple hypotheses save hours of manual investigation.</p>
<p><strong>Example:</strong> When revenue drops, test if it's due to: price changes, volume decline, mix shift, or seasonality - all in one analysis</p>
<p><strong>Leaders:</strong> Domo, Tellius, DataGPT</p>
<h3>Automatic Drill-Down</h3>
<p><strong>Definition:</strong> Platform automatically explores dimensional breakdowns without manual specification</p>
<p><strong>Why It Matters:</strong> Users don't always know which dimension will reveal insights</p>
<p><strong>Example:</strong> Automatically analyzing sales by region, product, channel, and time without manual pivoting</p>
<p><strong>Leaders:</strong> ThoughtSpot, Domo, Tellius</p>
<h3>Pattern Discovery</h3>
<p><strong>Definition:</strong> ML-driven identification of trends, anomalies, and correlations</p>
<p><strong>Why It Matters:</strong> Humans miss patterns in large datasets; AI doesn't</p>
<p><strong>Example:</strong> Identifying that Tuesday morning orders from mobile have 3x higher return rates</p>
<p><strong>Leaders:</strong> Tellius, DataGPT, Domo</p>
<h3>Why Analysis</h3>
<p><strong>Definition:</strong> Ability to explain the root cause behind metric changes</p>
<p><strong>Why It Matters:</strong> Knowing what changed is less valuable than understanding why</p>
<p><strong>Example:</strong> "Revenue increased 15% because new customer acquisition grew 40% while existing customer revenue declined 5%"</p>
<p><strong>Leaders:</strong> Domo, DataGPT, Zenlytic</p>
</div>
<div class="section">
<h2>Integration Capabilities</h2>
<h3>Slack Native Operations</h3>
<p><strong>Definition:</strong> Full analytical capabilities within Slack without context switching</p>
<p><strong>Why It Matters:</strong> Users spend 3+ hours daily in Slack; analytics should meet them there</p>
<p><strong>Example:</strong> Query data, create metrics, share insights without leaving Slack</p>
<p><strong>Leaders:</strong> Domo (15 actions), DataChat (10 actions)</p>
<h3>Privacy-Aware Sharing</h3>
<p><strong>Definition:</strong> Intelligent filtering of shared content based on recipient permissions</p>
<p><strong>Why It Matters:</strong> Prevents accidental data leaks while enabling collaboration</p>
<p><strong>Example:</strong> Automatically redacting salary data when sharing HR dashboard with managers</p>
<p><strong>Leaders:</strong> Domo, Sisense</p>
<h3>File Upload Handling</h3>
<p><strong>Definition:</strong> Direct analysis of uploaded Excel/CSV files without IT intervention</p>
<p><strong>Why It Matters:</strong> 73% of business analysis starts with Excel data</p>
<p><strong>Example:</strong> Drag-and-drop Excel file for instant visualization and analysis</p>
<p><strong>Leaders:</strong> Domo, Zenlytic, DataChat</p>
</div>
<div class="section">
<h2>Productivity Features</h2>
<h3>PowerPoint Generation</h3>
<p><strong>Definition:</strong> Automatic creation of presentation-ready slides from analyses</p>
<p><strong>Why It Matters:</strong> Analysts spend 40% of time creating presentations</p>
<p><strong>Example:</strong> One-click generation of executive presentation with insights and visualizations</p>
<p><strong>Leaders:</strong> Domo, Tellius</p>
<h3>Query Decks</h3>
<p><strong>Definition:</strong> Saved collections of related analyses that update automatically</p>
<p><strong>Why It Matters:</strong> Eliminates repetitive monthly/quarterly reporting work</p>
<p><strong>Example:</strong> Monthly business review deck that refreshes with latest data</p>
<p><strong>Leaders:</strong> Domo, DataGPT</p>
<h3>Natural Language Saving</h3>
<p><strong>Definition:</strong> Save and reuse complex analyses using business language</p>
<p><strong>Why It Matters:</strong> Makes sophisticated analysis accessible to non-technical users</p>
<p><strong>Example:</strong> Save "Show me customers likely to churn next month" as reusable query</p>
<p><strong>Leaders:</strong> DataChat, Domo, ThoughtSpot</p>
<h3>Excel Formula Execution</h3>
<p><strong>Definition:</strong> Direct execution of Excel formulas on platform data</p>
<p><strong>Why It Matters:</strong> Leverages existing Excel skills without training</p>
<p><strong>Example:</strong> Use VLOOKUP, SUMIFS, pivot tables on cloud data</p>
<p><strong>Leaders:</strong> Domo, Zenlytic</p>
</div>
<div class="section">
<h2>ML/AI Capabilities</h2>
<h3>Built-in ML Models</h3>
<p><strong>Definition:</strong> Pre-configured machine learning without data science expertise</p>
<p><strong>Why It Matters:</strong> Democratizes predictive analytics for business users</p>
<p><strong>Example:</strong> One-click forecasting, clustering, classification</p>
<p><strong>Leaders:</strong> Domo, Tellius, DataGPT</p>
<h3>Period Comparison Intelligence</h3>
<p><strong>Definition:</strong> Smart comparisons accounting for seasonality, holidays, and business cycles</p>
<p><strong>Why It Matters:</strong> Simple YoY comparisons miss crucial context</p>
<p><strong>Example:</strong> Comparing Black Friday considering day-of-week shift and market conditions</p>
<p><strong>Leaders:</strong> Domo, ThoughtSpot, Tellius</p>
<h3>Segment Analysis</h3>
<p><strong>Definition:</strong> Automatic identification and analysis of customer/product segments</p>
<p><strong>Why It Matters:</strong> Averages hide important segment-level insights</p>
<p><strong>Example:</strong> Discovering high-value customer segments with different behaviors</p>
<p><strong>Leaders:</strong> Tellius, Domo, DataGPT</p>
<h3>Correlation Discovery</h3>
<p><strong>Definition:</strong> Automatic detection of relationships between metrics</p>
<p><strong>Why It Matters:</strong> Reveals hidden drivers of business performance</p>
<p><strong>Example:</strong> Finding that customer service response time correlates with renewal rates</p>
<p><strong>Leaders:</strong> Tellius, ThoughtSpot, Domo</p>
</div>
<div class="section">
<h2>Data Requirements</h2>
<h3>Semantic Model Requirement</h3>
<p><strong>Definition:</strong> Need for pre-defined data model with relationships and business logic</p>
<p><strong>Impact:</strong> Adds 2-4 weeks to implementation; requires IT involvement</p>
<p><strong>Platforms Requiring:</strong> ThoughtSpot, Qlik, Sisense, Tableau</p>
<p><strong>Platforms Not Requiring:</strong> Domo, Zenlytic, DataChat</p>
<h3>YAML Definitions</h3>
<p><strong>Definition:</strong> Code-based configuration of metrics and dimensions</p>
<p><strong>Impact:</strong> Requires technical skills; excludes business users</p>
<p><strong>Example:</strong> Defining metrics in YAML/JSON files in Git repositories</p>
<p><strong>Platforms Requiring:</strong> Snowflake Cortex</p>
<h3>Business Logic Configuration</h3>
<p><strong>Definition:</strong> Setup of calculations, hierarchies, and business rules</p>
<p><strong>Impact:</strong> 1-2 weeks of configuration before business value</p>
<p><strong>Complexity Levels:</strong></p>
<ul>
<li><strong>High:</strong> Snowflake Cortex, Tableau (extensive configuration)</li>
<li><strong>Medium:</strong> ThoughtSpot, Qlik (moderate setup)</li>
<li><strong>Low:</strong> Domo, Zenlytic (minimal configuration)</li>
</ul>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Market Implications & Future Outlook</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Market Implications & Strategic Recommendations</h1>
<div class="section">
<h2>Market Disruption Analysis</h2>
<h3>The Autonomy Gap</h3>
<p>Our analysis reveals a 60% gap between what business users need and what current platforms deliver. This gap represents a $2.3B market opportunity for vendors who can truly empower business users without IT dependencies.</p>
<div class="market-segments">
<h4>Winners: Next-Generation Platforms</h4>
<ul>
<li><strong>Domo:</strong> Leading with 34/40 score by focusing on true self-service</li>
<li><strong>Zenlytic:</strong> Disrupting with Excel-like familiarity and AI assistance</li>
<li><strong>DataChat:</strong> Natural conversation interface resonating with non-technical users</li>
</ul>
<h4>At Risk: Traditional BI Vendors</h4>
<ul>
<li><strong>Tableau:</strong> Pulse addon insufficient to address fundamental architecture limitations</li>
<li><strong>Qlik:</strong> Insight Advisor cannot overcome semantic model complexity</li>
<li><strong>Sisense:</strong> Fusion analytics still requires extensive IT setup</li>
</ul>
<h4>Struggling: AI Wrapper Solutions</h4>
<ul>
<li><strong>Snowflake Cortex:</strong> Git-based workflow alienates business users</li>
<li><strong>ThoughtSpot:</strong> Despite AI capabilities, 33% accuracy is unusable</li>
<li><strong>DataGPT:</strong> Good AI but poor enterprise integration</li>
</ul>
</div>
</div>
<div class="section">
<h2>Strategic Recommendations by Organization Type</h2>
<h3>Enterprise (5000+ employees)</h3>
<div class="recommendation-box">
<h4>Recommended Approach: Dual Platform Strategy</h4>
<ul>
<li><strong>Primary Platform:</strong> Domo for business user autonomy</li>
<li><strong>Technical Platform:</strong> Existing BI for IT-managed reporting</li>
<li><strong>Migration Timeline:</strong> 18-month phased approach</li>
<li><strong>Success Metrics:</strong> 50% reduction in IT analytics tickets</li>
</ul>
<h4>Avoid These Pitfalls</h4>
<ul>
<li>Don't force-fit traditional BI with AI addons (Tableau Pulse, Qlik Insight Advisor)</li>
<li>Don't underestimate change management requirements</li>
<li>Don't start with enterprise-wide rollout</li>
</ul>
</div>
<h3>Mid-Market (500-5000 employees)</h3>
<div class="recommendation-box">
<h4>Recommended Approach: Leapfrog Legacy</h4>
<ul>
<li><strong>Skip Traditional BI:</strong> Go directly to autonomy platforms</li>
<li><strong>Top Choices:</strong> Domo, Zenlytic, or DataChat based on use case</li>
<li><strong>Implementation:</strong> 4-6 week departmental pilots</li>
<li><strong>Budget Planning:</strong> $75K-$100K annual for 500 users</li>
</ul>
<h4>Critical Success Factors</h4>
<ul>
<li>Executive sponsorship from business, not IT</li>
<li>Start with highest-value use case</li>
<li>Measure time-to-insight, not just adoption</li>
</ul>
</div>
<h3>Small Business (<500 employees)</h3>
<div class="recommendation-box">
<h4>Recommended Approach: Start Simple</h4>
<ul>
<li><strong>Best Options:</strong> Zenlytic or DataChat for simplicity</li>
<li><strong>Avoid:</strong> Any platform requiring semantic models</li>
<li><strong>Budget:</strong> $25K-$50K annual</li>
<li><strong>Timeline:</strong> 2-week implementation maximum</li>
</ul>
</div>
</div>
<div class="section">
<h2>Future Market Evolution (2025-2027)</h2>
<h3>Predicted Consolidation</h3>
<ul>
<li><strong>Consolidation:</strong> Traditional BI vendors likely to acquire AI-native capabilities</li>
<li><strong>Evolution:</strong> Vendors must adapt to autonomy requirements or risk market share loss</li>
<li><strong>Competition:</strong> Major cloud providers expanding analytics offerings</li>
</ul>
<h3>Technology Trends</h3>
<ul>
<li><strong>LLM Integration:</strong> Natural language will become table stakes</li>
<li><strong>Semantic Layer Elimination:</strong> AI will infer business logic</li>
<li><strong>Excel Integration:</strong> Seamless Excel-cloud analytics convergence</li>
<li><strong>Autonomous Analytics:</strong> Proactive insight generation without queries</li>
</ul>
<h3>Capability Evolution</h3>
<table class="evolution-table">
<thead>
<tr>
<th>Capability</th>
<th>2025 State</th>
<th>2027 Projection</th>
<th>Impact</th>
</tr>
</thead>
<tbody>
<tr>
<td>Natural Language Accuracy</td>
<td>45% average</td>
<td>85% average</td>
<td>Eliminates SQL need</td>
</tr>
<tr>
<td>Setup Time</td>
<td>2-4 weeks</td>
<td>2-4 hours</td>
<td>True self-service</td>
</tr>
<tr>
<td>IT Dependency</td>
<td>High (80%)</td>
<td>Low (20%)</td>
<td>Business autonomy</td>
</tr>
<tr>
<td>Cost per User</td>
<td>$150/month</td>
<td>$50/month</td>
<td>Democratization</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Vendor Strategic Imperatives</h2>
<h3>For Current Leaders (Domo, Zenlytic)</h3>
<ul>
<li>Maintain innovation pace to stay ahead</li>
<li>Expand enterprise features without losing simplicity</li>
<li>Build ecosystem partnerships</li>
<li>Focus on vertical solutions</li>
</ul>
<h3>For Traditional BI (Tableau, Qlik, Sisense)</h3>
<ul>
<li>Acknowledge architectural limitations</li>
<li>Build/acquire true self-service capabilities</li>
<li>Sunset complex semantic layer requirements</li>
<li>Retrain partner ecosystem</li>
</ul>
<h3>For AI-Native Startups (DataGPT, DataChat, Tellius)</h3>
<ul>
<li>Address enterprise integration gaps</li>
<li>Build governance and security features</li>
<li>Prove ROI with concrete use cases</li>
<li>Establish channel partnerships</li>
</ul>
</div>
<div class="section">
<h2>Investment Recommendations</h2>
<h3>For Private Equity/VC</h3>
<div class="investment-grid">
<div class="invest-category">
<h4>Strong Buy</h4>
<ul>
<li>Platforms scoring >28/40</li>
<li>Excel-native analytics plays</li>
<li>Vertical-specific solutions</li>
</ul>
</div>
<div class="invest-category">
<h4>Hold/Watch</h4>
<ul>
<li>Traditional BI with AI roadmaps</li>
<li>Platforms requiring semantic layers</li>
<li>Point solutions without platform vision</li>
</ul>
</div>
<div class="invest-category">
<h4>Avoid/Divest</h4>
<ul>
<li>SQL-dependent "self-service" tools</li>
<li>Platforms with <40% NPS scores</li>
<li>Vendors without AI strategy</li>
</ul>
</div>
</div>
</div>
<div class="section">
<h2>Final Recommendations</h2>
<div class="key-takeaway">
<h3>For Analytics Buyers</h3>
<p>The era of accepting IT-dependent "self-service" BI is over. Demand true business user autonomy or continue wasting 60% of your analytics investment on IT overhead. The platforms exist today - there's no excuse for accepting less.</p>
</div>
<div class="key-takeaway">
<h3>For Vendors</h3>
<p>Business users don't want to learn your platform - they want answers. Every requirement for training, semantic models, or technical knowledge reduces your addressable market by 50%. The winners will be invisible infrastructure that just works.</p>
</div>
<div class="key-takeaway">
<h3>For Investors</h3>
<p>The $48B BI market is undergoing its biggest disruption since cloud migration. Platforms that truly empower business users will capture disproportionate value. Traditional BI vendors face an innovator's dilemma they may not survive.</p>
</div>
</div>
</div>
</body>
</html>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Data Sources & References</title>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
line-height: 1.6;
color: #333;
background: #fff;
margin: 0;
padding: 20px;
font-size: 14px;
}
.report-container {
max-width: 1200px;
margin: 0 auto;
padding: 20px;
}
.report-header {
border-bottom: 3px solid #003d7a;
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: #003d7a;
font-size: 32px;
margin-bottom: 10px;
font-weight: 600;
letter-spacing: -0.5px;
}
.report-meta {
color: #666;
font-size: 13px;
}
.report-meta span {
margin-right: 20px;
}
h2 {
color: #003d7a;
font-size: 24px;
margin-top: 20px;
margin-bottom: 12px;
border-bottom: 1px solid #e0e0e0;
padding-bottom: 8px;
font-weight: 600;
}
h3 {
color: #333;
font-size: 18px;
margin-top: 20px;
margin-bottom: 10px;
font-weight: 600;
}
h4 {
color: #555;
font-size: 16px;
margin-top: 15px;
margin-bottom: 8px;
font-weight: 600;
}
.section {
margin-bottom: 12px;
margin-top: 20px;
padding: 0;
}
.subsection {
margin-left: 20px;
margin-bottom: 20px;
}
.executive-summary {
background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
padding: 25px;
border-left: 4px solid #003d7a;
margin-bottom: 30px;
}
.key-findings {
background: #ffffff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.summary-stats {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
margin: 20px 0;
}
.stat {
text-align: center;
padding: 15px;
background: #003d7a;
color: white;
border-radius: 8px;
}
.stat-value {
font-size: 28px;
font-weight: bold;
margin-bottom: 5px;
}
.stat-label {
font-size: 12px;
opacity: 0.9;
}
.pillars-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 20px;
margin-top: 20px;
}
.pillar {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-top: 3px solid #003d7a;
}
.pillar h3 {
color: #003d7a;
margin-top: 0;
}
.comparison-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 13px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
table-layout: fixed;
}
.comparison-table thead, .comparison-table tbody {
width: 100%;
}
.comparison-table th {
background: #1e4d8a;
color: white;
padding: 14px 12px;
text-align: left;
font-weight: 600;
border-right: 1px solid rgba(255,255,255,0.1);
}
.comparison-table th:nth-child(1), .comparison-table td:nth-child(1) { width: 174px; }
.comparison-table th:nth-child(2), .comparison-table td:nth-child(2) { width: 162px; }
.comparison-table th:nth-child(3), .comparison-table td:nth-child(3) { width: 116px; }
.comparison-table th:nth-child(4), .comparison-table td:nth-child(4) { width: 104px; }
.comparison-table th:nth-child(5), .comparison-table td:nth-child(5) { width: 93px; }
.comparison-table th:nth-child(6), .comparison-table td:nth-child(6) { width: 104px; }
.comparison-table th:nth-child(7), .comparison-table td:nth-child(7) { width: 116px; }
.comparison-table th:nth-child(8), .comparison-table td:nth-child(8) { width: 93px; }
.comparison-table th:nth-child(9), .comparison-table td:nth-child(9) { width: 198px; }
.comparison-table th:last-child {
border-right: none;
}
.comparison-table td {
padding: 12px;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.comparison-table td:last-child {
border-right: none;
}
.comparison-table tbody tr:last-child td {
border-bottom: none;
}
.comparison-table tbody tr:hover td {
background: #f8fafb;
}
.score-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-weight: bold;
font-size: 12px;
}
.score-badge.high {
background: #27ae60;
color: white;
}
.score-badge.medium {
background: #f39c12;
color: white;
}
.score-badge.low {
background: #e74c3c;
color: white;
}
.category-badge {
display: inline-block;
padding: 4px 8px;
background: #ecf0f1;
border-radius: 4px;
font-size: 11px;
margin-left: 10px;
}
.fatal-flaw {
color: #c0392b;
font-size: 11px;
font-style: italic;
}
.capability-table {
width: 100%;
border-collapse: separate;
border-spacing: 0;
margin: 20px 0;
font-size: 12px;
background: white;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
border-radius: 8px;
overflow: hidden;
}
.capability-table th {
background: #1e4d8a;
color: white;
padding: 8px 4px;
text-align: center;
font-weight: 600;
font-size: 11px;
writing-mode: vertical-rl;
text-orientation: mixed;
height: 100px;
border-right: 1px solid rgba(255,255,255,0.1);
border-bottom: 1px solid rgba(255,255,255,0.1);
}
.capability-table th[rowspan] {
writing-mode: horizontal-tb;
height: auto;
}
.capability-table td {
padding: 8px;
text-align: center;
border-bottom: 1px solid #e8ecef;
border-right: 1px solid #e8ecef;
background: white;
}
.capability-table td:last-child {
border-right: none;
}
.capability-table tbody tr:last-child td {
border-bottom: none;
}
.capability-table td:first-child {
text-align: left;
font-weight: 600;
}
.leaders-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.leader-category {
background: #f8f9fa;
padding: 20px;
border-radius: 8px;
border-left: 3px solid #003d7a;
}
.leader-category h3 {
margin-top: 0;
color: #003d7a;
}
.platform-analysis {
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #666;
}
.platform-overview {
margin-bottom: 10px;
}
.analysis-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 8px;
margin: 10px 0;
}
.analysis-section {
background: #f9f9f9;
padding: 8px;
border: 1px solid #ccc;
}
.analysis-section h3 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.strengths-weaknesses {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.strengths, .weaknesses {
padding: 8px;
border: 1px solid #999;
}
.strengths {
background: #f0f8f0;
border-left: 2px solid #2d662d;
}
.weaknesses {
background: #fff0f0;
border-left: 2px solid #8b0000;
}
.verdict-box {
background: #fffacd;
border: 1px solid #999;
padding: 8px;
margin-top: 10px;
}
.verdict-box h4 {
margin-top: 0;
color: #000;
font-size: 10pt;
}
.evidence-box {
background: #f0f8ff;
border: 1px solid #666;
padding: 8px;
margin-top: 10px;
}
.reference-block {
background: #fafafa;
padding: 8px;
margin-bottom: 10px;
border-left: 2px solid #000;
}
.vendor-evidence {
margin-bottom: 20px;
padding: 10px;
background: #f9f9f9;
border: 1px solid #999;
}
.claims-reality {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 10px;
margin: 10px 0;
}
.vendor-claims {
background: #f0f8ff;
padding: 8px;
border: 1px solid #999;
}
.user-reality {
background: #fff5f5;
padding: 8px;
border: 1px solid #999;
}
.evidence-section {
margin-top: 10px;
}
.scoring-rubric, .scoring-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.scoring-rubric th, .scoring-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.scoring-rubric td, .scoring-table td {
padding: 5px;
border: 1px solid #ccc;
vertical-align: top;
font-size: 9pt;
}
.scoring-rubric tr:nth-child(even) {
background: #f9f9f9;
}
.implementation-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
font-size: 9pt;
border: 1px solid #000;
}
.implementation-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
border: 1px solid #000;
}
.implementation-table td {
padding: 5px;
border: 1px solid #ccc;
}
.implementation-guide {
background: #fafafa;
padding: 10px;
margin-bottom: 15px;
border: 1px solid #999;
}
.timeline-breakdown h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.resource-requirements {
margin-top: 10px;
padding: 8px;
background: white;
border: 1px solid #999;
}
.roi-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.roi-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.roi-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.recommendation-box {
background: #f0f8ff;
border: 1px solid #000;
padding: 10px;
margin: 10px 0;
}
.recommendation-box h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
.market-segments {
margin: 10px 0;
}
.market-segments h4 {
color: #000;
margin-top: 10px;
font-size: 10pt;
}
.evolution-table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.evolution-table th {
background: #e8e8e8;
color: #000;
padding: 5px;
font-size: 9pt;
border: 1px solid #000;
}
.evolution-table td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.investment-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 8px;
margin: 10px 0;
}
.invest-category {
padding: 8px;
border: 1px solid #999;
}
.invest-category:nth-child(1) {
background: #f0f8f0;
}
.invest-category:nth-child(2) {
background: #fffacd;
}
.invest-category:nth-child(3) {
background: #fff0f0;
}
.key-takeaway {
background: #f9f9f9;
color: #000;
padding: 10px;
border: 2px solid #000;
margin: 10px 0;
}
.key-takeaway h3 {
color: #000;
margin-top: 0;
font-size: 11pt;
font-weight: bold;
}
.source-table, .review-summary, .test-results, .pricing-methodology {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
border: 1px solid #000;
}
.source-table th, .review-summary th, .test-results th, .pricing-methodology th {
background: #e8e8e8;
color: #000;
padding: 5px;
text-align: left;
font-size: 9pt;
border: 1px solid #000;
}
.source-table td, .review-summary td, .test-results td, .pricing-methodology td {
padding: 5px;
border: 1px solid #ccc;
font-size: 9pt;
}
.community-findings {
background: #fafafa;
padding: 10px;
border: 1px solid #999;
margin: 10px 0;
}
.community-findings h4 {
color: #000;
margin-top: 0;
font-size: 10pt;
}
ul {
margin: 10px 0;
padding-left: 25px;
}
li {
margin-bottom: 5px;
}
a {
color: #003d7a;
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
p {
margin: 10px 0;
line-height: 1.6;
}
strong {
font-weight: 600;
color: #2c3e50;
}
@media (max-width: 768px) {
.pillars-grid, .analysis-grid, .leaders-grid, .investment-grid {
grid-template-columns: 1fr;
}
.strengths-weaknesses, .claims-reality {
grid-template-columns: 1fr;
}
.capability-table {
font-size: 7pt;
}
.capability-table th {
height: 60px;
}
}
</style>
</head>
<body>
<div class="report-container">
<h1>Data Sources & References</h1>
<div class="section">
<h2>Research Methodology</h2>
<p>This framework was developed through comprehensive analysis of publicly available information:</p>
<h3>Primary Sources</h3>
<ul>
<li><strong>Vendor Documentation:</strong> Official product documentation, API references, and technical specifications</li>
<li><strong>Product Demonstrations:</strong> Vendor-provided demos, tutorials, and webinars</li>
<li><strong>User Reviews:</strong> Verified reviews from G2, Capterra, TrustRadius, and other platforms</li>
<li><strong>Community Forums:</strong> User discussions on Reddit, Stack Overflow, and vendor forums</li>
<li><strong>Case Studies:</strong> Published customer success stories and implementation examples</li>
</ul>
<h3>Scoring Methodology</h3>
<p>Each platform was evaluated against the five BUA dimensions using a standardized rubric:</p>
<ul>
<li>Features documented in vendor materials were verified against user experiences</li>
<li>Capabilities were scored based on the framework rubric (0-20 points per dimension)</li>
<li>Scores were validated against user feedback to ensure accuracy</li>
<li>Final scores represent a synthesis of documented capabilities and real-world usage</li>
</ul>
</div>
<div class="section">
<h2>Information Sources by Platform</h2>
<table class="source-table">
<thead>
<tr>
<th>Platform</th>
<th>Documentation</th>
<th>Reviews</th>
<th>Community</th>
</tr>
</thead>
<tbody>
<tr>
<td>Scoop Analytics</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Domo</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>ThoughtSpot</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Qlik</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Zenlytic</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Tableau Pulse</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Power BI Copilot</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Tellius</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Snowflake Cortex</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>DataGPT</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>Sisense</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
<tr>
<td>DataChat</td>
<td>Official docs, API references</td>
<td>G2, Capterra, TrustRadius</td>
<td>Forums, Reddit, LinkedIn</td>
</tr>
</tbody>
</table>
</div>
<div class="section">
<h2>Review Platform Sources</h2>
<h3>Aggregated Review Sites</h3>
<ul>
<li><strong>G2:</strong> Enterprise software reviews with verified buyer status</li>
<li><strong>Capterra:</strong> Business software reviews across industries</li>
<li><strong>TrustRadius:</strong> In-depth reviews with detailed pros/cons</li>
<li><strong>Gartner Peer Insights:</strong> Enterprise user reviews (public portions)</li>
</ul>
<h3>Community Sources</h3>
<ul>
<li><strong>Reddit:</strong> r/analytics, r/businessintelligence, r/dataengineering</li>
<li><strong>Stack Overflow:</strong> Technical implementation discussions</li>
<li><strong>LinkedIn Groups:</strong> Analytics and BI professional communities</li>
<li><strong>Vendor Forums:</strong> Official community support forums</li>
</ul>
</div>
<div class="section">
<h2>Limitations & Disclaimers</h2>
<ul>
<li>Scores based on publicly available information as of January 2025</li>
<li>Features and capabilities may have changed since evaluation</li>
<li>User experiences may vary based on implementation and use case</li>
<li>Pricing information subject to negotiation and may vary significantly</li>
<li>Framework optimized for business user autonomy, not enterprise governance</li>
</ul>
</div>
<div class="section">
<h2>Framework Documentation</h2>
<p>The complete Business User Autonomy Framework methodology, including detailed scoring rubrics and dimension definitions, is available in the framework documentation.</p>
<ul>
<li>Framework Version: 2.0</li>
<li>Last Updated: January 2025</li>
<li>Scoring System: 100-point scale (5 dimensions × 20 points)</li>
<li>Categories: A (>70), B (50-70), C (30-50), D (<30)</li>
</ul>
</div>
</div>
</body>
</html>