<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;500;600;700&display=swap" rel="stylesheet">
<style>
section.hero--3way { padding: 40px 20px; background: linear-gradient(180deg, #ffffff 0%, #f8f9fd 100%) !important; }
.hero__container { max-width: 1200px; margin: 0 auto; }
.hero__eyebrow { font-weight: 600; font-size: 14px; color: #4763F5; text-transform: uppercase; letter-spacing: 1px; margin-bottom: 16px; text-align: center; }
.hero__title { font-weight: 600; font-size: 46px; line-height: 1.1; color: #130417; margin-bottom: 24px; text-align: center; }
.hero__scores { display: grid; grid-template-columns: repeat(3, 1fr); gap: 32px; margin-bottom: 32px; }
.score-card { background: #ffffff; border-radius: 12px; padding: 24px; box-shadow: 0 4px 16px rgba(0,0,0,0.08); text-align: center; }
.score-card--scoop { border: 2px solid #4763F5; background: linear-gradient(135deg, #f0f3ff 0%, #f8f9ff 100%); }
.score-card__name { font-weight: 600; font-size: 18px; color: #130417; margin-bottom: 12px; }
.score-card__score { font-weight: 700; font-size: 42px; margin-bottom: 8px; }
.score-card--scoop .score-card__score { color: #4763F5; }
.score-card--competitor .score-card__score { color: #E3165B; }
.score-card__label { font-size: 14px; color: #666; }
.score-card__badge { display: inline-block; background: #4763F5; color: white; padding: 4px 12px; border-radius: 20px; font-size: 12px; font-weight: 600; margin-top: 8px; }
section.content-section { padding: 32px 20px; background: #ffffff !important; }
section.content-section--alt { background: #f8f9fd !important; }
.content-section__container { max-width: 1000px; margin: 0 auto; }
.content-section__title { font-weight: 600; font-size: 36px; color: #130417; margin-bottom: 20px; }
.content-section__subsection { margin-bottom: 32px; }
.content-section__subtitle { font-weight: 600; font-size: 24px; color: #130417; margin-bottom: 12px; }
.content-section__paragraph { font-weight: 400; font-size: 16px; line-height: 1.6; color: #333333; margin-bottom: 12px; }
.content-section__list { margin: 16px 0 16px 20px; padding-left: 0; list-style-type: disc; color: #333333; }
.content-section__list-item { font-weight: 400; font-size: 16px; line-height: 1.6; margin-bottom: 8px; }
.content-section__table { width: 100%; border-collapse: collapse; margin: 24px 0; background: #ffffff; border-radius: 8px; overflow: hidden; box-shadow: 0 2px 8px rgba(0,0,0,0.06); }
.content-section__table th { background: #4763F5; color: #ffffff; font-weight: 600; font-size: 14px; text-align: left; padding: 16px; }
.content-section__table td { padding: 14px 16px; border-bottom: 1px solid #e5e5e5; font-size: 14px; color: #333333; }
.content-section__table tr:last-child td { border-bottom: none; }
.content-section__table tr:hover { background: #f8f9fd; }
.comparison-table--3way th:first-child { width: 30%; }
.comparison-table--3way th:nth-child(2),
.comparison-table--3way th:nth-child(3),
.comparison-table--3way th:nth-child(4) { width: 23.33%; }
.winner-cell { background: #f0fff4; font-weight: 600; color: #333333; }
.loser-cell { background: #fff5f5; color: #333333; }
.scoop-cell { background: #f0f3ff; font-weight: 600; color: #333333; }
section.cta-section { padding: 100px 20px; background: linear-gradient(135deg, #4763F5 0%, #3651D4 100%) !important; text-align: center; color: #ffffff; }
.cta-section__title { font-weight: 600; font-size: 36px; margin-bottom: 16px; }
.cta-section__subtitle { font-weight: 400; font-size: 18px; margin-bottom: 32px; opacity: 0.9; }
.btn--primary { font-weight: 500; font-size: 16px; padding: 14px 28px; background: #ffffff; color: #4763F5; text-decoration: none; border-radius: 8px; display: inline-block; box-shadow: 0 2px 8px rgba(255,255,255,0.3); transition: all 0.2s ease; }
.btn--primary:hover { transform: translateY(-2px); box-shadow: 0 4px 16px rgba(255,255,255,0.4); }
.faq-section { padding: 60px 20px; background: #f8f9fd; }
.faq-section__container { max-width: 900px; margin: 0 auto; }
.faq-section__title { font-weight: 600; font-size: 36px; text-align: center; color: #130417; margin-bottom: 40px; }
.faq-item { background: #ffffff; border-radius: 12px; padding: 28px; margin-bottom: 16px; box-shadow: 0 2px 8px rgba(0,0,0,0.06); }
.faq-item__question { font-weight: 600; font-size: 18px; color: #130417; margin-bottom: 12px; }
.faq-item__answer { font-weight: 400; font-size: 16px; color: #666666; line-height: 1.6; }
</style>
<section class="hero--3way">
<div class="hero__container">
<div class="hero__eyebrow">AI-POWERED COMPARISON</div>
<h1 class="hero__title">Power BI Copilot vs Tellius vs Scoop: Complete Comparison</h1>
<div class="hero__scores">
<div class="score-card score-card--competitor">
<div class="score-card__name">Power BI Copilot</div>
<div class="score-card__score">32/100</div>
<div class="score-card__label">BUA Score</div>
</div>
<div class="score-card score-card--competitor">
<div class="score-card__name">Tellius</div>
<div class="score-card__score">22/100</div>
<div class="score-card__label">BUA Score</div>
</div>
<div class="score-card score-card--scoop">
<div class="score-card__name">Scoop Analytics</div>
<div class="score-card__score">82/100</div>
<div class="score-card__label">BUA Score</div>
<div class="score-card__badge">WINNER ✓</div>
</div>
</div>
</div>
</section>
<section class="content-section ">
<div class="content-section__container">
<h2 class="content-section__title">Executive Summary</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">TL;DR Verdict</h3>
<p class="content-section__paragraph">Scoop (82/100 BUA) enables true business autonomy through multi-pass investigation, while Power BI Copilot (32/100) and Tellius (22/100) trap users in dashboard paradigms. Both competitors fail at iterative questioning, forcing business users back to IT for every new insight. Choose Scoop for immediate independence, competitors only within existing Microsoft or augmented analytics commitments.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">What is Scoop?</h3>
<p class="content-section__paragraph">Scoop is an AI data analyst you chat with, not another dashboard tool. Ask questions in plain English and get answers with charts instantly. Works natively in Excel and Slack where business users already work. No SQL, no training, no semantic layer maintenance ever required.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Choose Scoop If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You need multi-pass investigation (3-10 follow-up questions) without IT involvement</li>
<li class="content-section__list-item">Business users work primarily in Excel and need instant data access</li>
<li class="content-section__list-item">You want to eliminate consultant dependencies and training costs permanently</li>
<li class="content-section__list-item">Teams need answers in minutes, not dashboard development in weeks</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Power BI Copilot If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You're deeply invested in Microsoft's ecosystem with existing Power BI infrastructure</li>
<li class="content-section__list-item">Your use cases are purely dashboard-based with no investigation needs</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Tellius If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You specifically need augmented analytics features like automated insights generation</li>
<li class="content-section__list-item">Your organization requires on-premise deployment with no cloud options</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Bottom Line</h3>
<p class="content-section__paragraph">The BUA scores reveal a fundamental truth: Scoop operates on a different paradigm than dashboard-centric competitors . The future belongs to platforms that empower business users to investigate independently, not prettier dashboards that still require IT mediation.</p>
</div>
</div>
</section>
<section class="content-section content-section--alt">
<div class="content-section__container">
<h2 class="content-section__title">At-a-Glance Comparison</h2>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Dimension</th><th>Power BI Copilot</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class=""><strong>BUA Score</strong></td><td class="">32/100</td><td class="">22/100</td><td class="scoop-cell">82/100</td>
</tr>
</tbody>
</table>
</div>
</section>
<section class="content-section ">
<div class="content-section__container">
<h2 class="content-section__title">BUA Framework Deep Dive</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Autonomy (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Autonomy</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Power BI Copilot</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">2/8</td><td class="">0/8</td><td class="">5/8</td>
</tr>
<tr>
<td class="">Investigation Depth</td><td class="">1/8</td><td class="">0/8</td><td class="">5/8</td>
</tr>
<tr>
<td class="">Setup Requirements</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Query Flexibility</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 18/20 on Autonomy versus Power BI Copilot's 7/20, delivering true self-service analytics. Business users ask questions naturally and investigate freely without IT help. Power BI Copilot requires semantic models and DAX measures, limiting users to pre-configured views. Scoop enables 3-10 question investigations immediately.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Flow (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Flow</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Power BI Copilot</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Native Integration</td><td class="">2/8</td><td class="">0/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">2/8</td><td class="">0/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Workflow Continuity</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 17/20 on Flow versus Power BI Copilot's 6/20 by living natively in Slack and Teams where business users work. Power BI Copilot requires portal switching that breaks workflow continuity. Scoop enables investigation without leaving conversations, eliminating 12-minute context switches.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Understanding (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Understanding</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Power BI Copilot</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Business Terminology</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Error Handling</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Context Awareness</td><td class="">1/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 16/20 on Understanding versus Power BI Copilot's 7/20, primarily due to natural language processing that doesn't require semantic layer knowledge. Business users can ask questions using their own terminology while Power BI Copilot requires exact measure names from its data model.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Presentation (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Presentation</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Power BI Copilot</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Output Format Flexibility</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Context-Aware Formatting</td><td class="">1/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Narrative Generation</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Share & Collaborate</td><td class="">1/8</td><td class="">0/8</td><td class="">3/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 15/20 on Presentation versus Power BI Copilot's 6/20, delivering complete analytical narratives with embedded charts while Power BI requires manual dashboard assembly. Scoop produces boardroom-ready insights directly; Power BI generates components needing extensive reformatting for executive consumption.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Data (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Data</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Power BI Copilot</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Data Connection Setup</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Source Flexibility</td><td class="">2/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Refresh Control</td><td class="">1/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Data Governance</td><td class="">1/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 16/20 on Data capabilities, allowing business users to connect data sources directly without IT help. Power BI Copilot scores 6/20, requiring IT-maintained semantic models before users can access data. Tellius wasn't scored. Scoop eliminates the 2-3 week wait for IT to add new data sources.</p>
</div>
</div>
</section>
<section class="content-section content-section--alt">
<div class="content-section__container">
<h2 class="content-section__title">Capability Deep Dive</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Investigation & Root Cause Analysis</h3>
<p class="content-section__paragraph">When revenue suddenly drops 15%, the difference between knowing it happened and understanding why separates great companies from the rest. Traditional BI shows you the drop on a dashboard. Investigation platforms help you find the root cause through iterative questioning—just like working with a skilled analyst. This capability determines whether business users can solve problems independently or need to file IT tickets for every 'why' question. The architectural difference between single-query tools and multi-pass investigation systems fundamentally changes how quickly organizations can respond to problems.</p>
<p class="content-section__paragraph">The fundamental divide lies in architecture. Power BI Copilot operates within Microsoft's semantic model constraints—you can only investigate what's been pre-modeled. Users hit walls when asking 'why' beyond the second level. Tellius brings genuine investigation capability through its AutoML engine, automatically testing hypotheses and finding statistical drivers. But users must learn its guided workflow system and specific terminology. Scoop treats investigation as conversation. Ask 'Why did sales drop?' and it checks seasonality, segments, and correlations automatically. Follow with 'What about competitor pricing?' and it maintains full context. No workflows to learn, no semantic models to maintain. The key metric reveals everything: queries to root cause. Power BI Copilot averages 8-10 queries with multiple dead ends. Tellius reaches answers in 4-5 guided steps. Scoop typically finds root causes in 3-4 conversational exchanges. This isn't about features—it's about whether business users can actually investigate problems independently. Power BI's semantic layer dependency means IT must pre-model every possible investigation path. Tellius requires training on its workflow system. Scoop works like talking to an analyst who already knows your business.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices conversion rates dropped 12% last week. With Scoop, she types: 'Why did conversion drop last week?' Scoop automatically investigates—checking traffic sources, device types, page performance, and inventory levels. It identifies that mobile checkout errors spiked after Tuesday's update. She asks: 'Which products were most affected?' Scoop shows high-value items had 3x higher abandonment. Total investigation: 3 minutes, 3 questions. With Power BI Copilot, she'd need to manually check each dimension, reference specific visuals, and couldn't ask 'why'—only 'what.' The semantic model wouldn't include error logs, so she'd need IT to add that data. Tellius would guide her through its investigation workflow, but she'd need to select 'root cause analysis,' choose variables, and interpret statistical outputs. The mobile errors might surface, but connecting them to specific products requires another workflow. The difference: Scoop investigations feel like problem-solving conversations. Others feel like database interrogations.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scoop enables true root cause investigation through natural conversation—3-4 questions to find why metrics changed. Power BI Copilot constrains users to pre-modeled data with limited follow-up capability. Tellius offers powerful investigation but requires learning guided workflows. For organizations serious about empowering business users to solve problems independently, conversational investigation beats structured querying every time.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Excel & Spreadsheet Integration</h3>
<p class="content-section__paragraph">Excel remains the world's most popular business intelligence tool, with 750 million users who already know how to use it. The real question isn't whether platforms integrate with Excel—it's how seamlessly business users can move between spreadsheet analysis and deeper data investigation. Most BI vendors treat Excel as an export destination. Modern platforms recognize it as the starting point where business questions originate. This fundamental difference shapes everything from add-in design to workflow integration.</p>
<p class="content-section__paragraph">The architectural divide becomes clear in Excel integration. Power BI Copilot requires users to understand the semantic model beneath their Excel add-in. You're not asking questions about your business—you're navigating a data model through DAX-aware queries. . Tellius treats Excel as an afterthought, offering only static exports that break the investigation flow. Users must leave Excel, run analysis in Tellius, export results, then manually recreate in Excel. . Scoop embeds a full natural language interface directly in Excel. Users type questions like 'What drove the revenue spike in March?' and get answers with charts, without leaving Excel. The key difference: Scoop brings the analyst to Excel rather than forcing Excel users to become analysts. This isn't about features—it's about respecting how 750 million people actually work. Power BI's approach assumes users will learn its paradigm. Scoop learns theirs.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A financial analyst is building the monthly board report in Excel. She notices an unusual variance in operating expenses. With Scoop's Excel add-in, she types 'What caused the 15% increase in OpEx this month?' directly in a sidebar. Scoop analyzes all expense categories, identifies that cloud infrastructure costs spiked, and shows that three new enterprise customers drove the increase. She clicks 'Insert to Sheet' and continues her report. Total disruption: 90 seconds. With Power BI, she'd need to open Power BI Desktop, navigate the data model, write a DAX query, export results, and manually integrate findings. With Tellius, she'd switch to the web platform, run the analysis, export to CSV, import to Excel, and format manually. The Scoop user finished her report while others are still switching applications.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Excel integration reveals each platform's philosophy. Power BI forces Excel to conform to its data model paradigm, requiring DAX knowledge even in spreadsheets. Tellius ignores Excel entirely, treating it as a destination for static exports. Scoop recognizes Excel as the business user's home base, embedding full natural language analytics without disrupting existing workflows. For the 750 million Excel users worldwide, only Scoop offers true integration without compromise.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Side-by-Side Scenario Analysis</h3>
<p class="content-section__paragraph">Business decisions rarely happen in isolation. When executives ask 'What happens if we raise prices 5% versus cutting costs 10%?', they need to see multiple scenarios simultaneously, not sequentially. This capability—running parallel what-if analyses—separates true analytical platforms from simple reporting tools. The difference isn't just convenience; it's about decision velocity. Teams that can instantly compare scenarios make decisions in hours, not days. Let's examine how Power BI Copilot, Tellius, and Scoop handle this fundamental business need.</p>
<p class="content-section__paragraph">The architectural divide becomes stark in scenario analysis. Power BI Copilot treats each scenario as a separate query, forcing users to mentally track differences across multiple screens. You ask about a 5% price increase, get a result, then separately query about 10%—losing visual comparison. Tellius offers scenario comparison but requires upfront configuration through their GUI, defining parameters before analysis begins. This works for known scenarios but fails when investigations evolve. Scoop's conversational architecture enables true branching: 'Show me revenue impact of 5% price increase' followed by 'Now show that alongside a 10% increase and 5% decrease.' The system maintains context, automatically generating side-by-side visualizations. More critically, Scoop remembers the investigation path. When you ask 'What drives the difference between scenarios?', it understands you mean the scenarios just discussed. Power BI Copilot has no such memory—each query starts fresh. This isn't just convenience; it's about investigation depth. Real business questions require 5-10 connected queries. Scoop handles this naturally through conversation. Power BI requires manual state management across queries. Tellius sits between—some context retention but requiring technical setup.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A CFO preparing for board meeting needs to present three budget scenarios: aggressive growth (20% marketing increase), conservative (maintain current), and defensive (15% cost reduction). With Scoop, she types: 'Compare revenue projections for 20% marketing increase, flat budget, and 15% cut.' Scoop generates three parallel projections with synchronized axes for easy comparison. She follows up: 'Add customer acquisition cost trends to each scenario.' The analysis updates instantly. Total time: 4 minutes. In Power BI Copilot, she'd need to create three separate queries, manually arrange visualizations, and rebuild when adding metrics. Tellius would require pre-defining scenario parameters in their interface before beginning analysis. When the board asks 'What if we do 10% increase instead?', Scoop adds it immediately. Power BI and Tellius require starting over.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scenario analysis reveals the investigation versus dashboard divide. Scoop treats scenarios as natural conversation branches, maintaining context across related questions. Power BI Copilot's single-query architecture forces sequential analysis without comparison capability. Tellius offers comparison features but requires technical setup that breaks business user flow. For teams making rapid decisions based on multiple scenarios, the difference is hours of productivity weekly.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Machine Learning & Pattern Discovery</h3>
<p class="content-section__paragraph">Your sales data contains hidden patterns that predict customer churn, forecast demand spikes, and reveal competitive threats. But discovering these insights shouldn't require a data science degree. The real question isn't whether a platform has ML capabilities—it's whether business users can actually use them. Let's examine how Power BI Copilot, Tellius, and Scoop democratize pattern discovery. The difference between automatic insights and manual model building determines whether your team spots opportunities in time to act on them.</p>
<p class="content-section__paragraph">Power BI Copilot treats ML as an add-on requiring Azure ML Studio integration and DAX expertise. Users see anomalies in visuals but can't ask 'why' without technical skills. Tellius brings legitimate ML capabilities with guided workflows and automated model selection. Their 'Genius Mode' runs statistical analysis across dimensions. But users still navigate menus and configure parameters. Scoop embeds ML invisibly into conversation. Ask 'What's driving customer churn?' and Scoop runs correlation analysis, checks seasonality, identifies patterns, and explains findings in business terms. No model selection. No parameter tuning. The architectural difference is fundamental. Power BI bolts ML onto dashboards. Tellius democratizes data science workflows. Scoop makes ML invisible—you ask questions, get answers with patterns automatically discovered. For business users, the distinction is critical. They don't want to 'do machine learning.' They want answers that happen to use ML. When a sales manager asks about unusual patterns, Scoop automatically runs anomaly detection, correlation analysis, and trend decomposition. Power BI shows the anomaly but requires manual investigation. Tellius offers tools but requires workflow knowledge.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices unusual inventory patterns across stores. With Scoop, she types: 'Find patterns in inventory turnover by store.' Scoop automatically segments stores by performance, identifies that Tuesday restocking correlates with 23% higher weekend sales, discovers that stores near competitors show different patterns, and highlights three locations with anomalous behavior. Total interaction: one question, complete analysis in 45 seconds. In Power BI Copilot, she'd need to create calculated measures for turnover, manually segment stores, build correlation matrices in DAX, and still wouldn't get the competitive proximity insight. Tellius would require selecting clustering algorithms, configuring parameters, and interpreting statistical outputs. The business impact is clear: Scoop delivers actionable patterns immediately, while competitors require either technical skills or data team support.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Machine learning should be invisible to business users—they want insights, not algorithms. Power BI Copilot requires technical configuration and Azure ML for serious pattern discovery. Tellius democratizes ML workflows but still demands statistical thinking. Scoop embeds ML throughout, automatically discovering patterns, testing correlations, and explaining findings in business language. The winner depends on your users: data analysts might appreciate Tellius's control, but business users need Scoop's invisible intelligence.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Workflow Integration & Mobile</h3>
<p class="content-section__paragraph">Modern data analysis happens everywhere—in Excel during budget planning, on phones during client meetings, in Slack when teams investigate issues. Yet most BI platforms treat workflow integration as an afterthought, forcing users to context-switch between tools. The real test isn't whether a platform has mobile apps or APIs. It's whether business users can get answers without leaving their natural workflow. Let's examine how each platform handles the reality of distributed, mobile-first teams who need data insights embedded in their daily tools, not trapped in separate portals.</p>
<p class="content-section__paragraph">The workflow integration divide reflects fundamental architecture choices. Power BI Copilot inherits Power BI's portal-centric design—you can export to Excel or view dashboards on mobile, but can't investigate. Their Excel integration means downloading static data, not live analysis. Mobile apps show pre-built reports without investigation capability. Tellius offers basic integrations but requires technical configuration. Their Slack bot accepts simple commands but can't handle multi-step investigations. Mobile access focuses on viewing existing analyses, not creating new ones. Scoop's chat-first architecture enables native workflow embedding. The Excel add-in brings full conversation capability into spreadsheets—ask follow-up questions, explore hypotheses, all without leaving Excel. Slack integration means entire teams investigate together in channels, preserving context and conclusions. Mobile works identically to desktop since it's just chat. The API is simply 'send question, get answer,' making custom integrations trivial. This isn't about having more integration points—it's about maintaining full analytical capability wherever users work. Traditional BI platforms treat integrations as viewers for centrally-created content. Scoop treats every integration point as a full analyst interface.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A sales director is reviewing quarterly forecasts in Excel when she spots an anomaly in the Southeast region. With Scoop's Excel add-in, she types directly in a sidebar: 'Why did Southeast bookings drop 30% last month?' Scoop investigates automatically, revealing a key account loss. She asks: 'What other accounts are at risk?' and gets a ranked list with churn indicators. She copies this insight to Slack where her team discusses retention strategies, with Scoop answering follow-up questions in the thread. Later, during a client dinner, she uses her phone to check: 'What's our win rate against Competitor X in enterprise deals?' Total context switches: zero. With Power BI Copilot, she'd need to leave Excel, open Power BI, build multiple queries, manually copy data back, and lose all context when switching devices. The mobile app would only show pre-built dashboards, not answer new questions.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Workflow integration isn't about checkboxes for mobile apps and APIs—it's about preserving analytical power wherever business users naturally work. While Power BI Copilot and Tellius treat integrations as viewing windows for centrally-created content, Scoop embeds a full AI analyst into Excel, Slack, and mobile. Business users investigate complex questions without leaving their tools, fundamentally changing how teams collaborate around data.</p>
</div>
</div>
</section>
<section class="content-section ">
<div class="content-section__container">
<h2 class="content-section__title">Frequently Asked Questions</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">What is Scoop?</h3>
<p class="content-section__paragraph">Scoop is an AI data analyst you chat with, not another dashboard. Ask questions in plain English, get answers with charts. Works natively in Excel and Slack. Unlike Power BI Copilot and Tellius which require IT setup, Scoop connects directly to your data in 30 seconds.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Which is better for business users: Power BI Copilot or Tellius?</h3>
<p class="content-section__paragraph">Neither empowers business users effectively. Power BI Copilot scores 32/100 on business autonomy, Tellius just 22/100. Both require IT support, semantic layers, and training. Scoop scores 82/100, letting business users investigate data independently. For true self-service analytics, neither traditional option suffices.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">How do I investigate anomalies in Power BI Copilot?</h3>
<p class="content-section__paragraph">Power BI Copilot can't investigate anomalies automatically. It answers single questions within existing reports, scoring just 6/20 for workflow capability. Real investigation requires manually chaining 3-10 queries, which Copilot doesn't support. You'll need IT to build custom reports for each anomaly type.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can Tellius do root cause analysis automatically?</h3>
<p class="content-section__paragraph">Tellius offers automated insights but requires extensive setup and model training first. Its 22/100 BUA score reflects heavy IT dependency. The AutoML features need data scientists to configure properly. Business users can't independently investigate new questions without pre-built models and semantic layer updates.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Scoop support multi-step analysis?</h3>
<p class="content-section__paragraph">Yes, Scoop automatically chains 3-10 queries for complete investigations. Ask why revenue dropped and Scoop explores segments, time periods, and correlations automatically. Unlike single-query tools like Power BI Copilot, Scoop thinks like an analyst, testing hypotheses until finding root causes.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">What does Power BI Copilot really cost including implementation?</h3>
<p class="content-section__paragraph">Power BI Copilot true cost includes licenses, implementation, training, maintenance, consultants, and productivity loss. Organizations typically spend 5-10x the license fee on these hidden costs. A $30/user license becomes $150-300/user monthly when including semantic layer maintenance and required IT support.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">How long does it take to learn Power BI Copilot?</h3>
<p class="content-section__paragraph">Power BI Copilot requires 2-4 weeks for basic proficiency. Users must understand Power BI's data model, DAX basics, and report structure. The 7/20 autonomy score reflects this learning curve. Even after training, complex questions require IT assistance or custom measure creation.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Do I need SQL knowledge for Tellius?</h3>
<p class="content-section__paragraph">While Tellius claims no SQL required, its 22/100 BUA score tells the real story. Complex analysis needs SQL for data preparation and custom calculations. The guided insights work only for pre-configured scenarios. Business users hit walls quickly without technical skills or IT support.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can business users use Scoop without IT help?</h3>
<p class="content-section__paragraph">Yes, business users connect Scoop to data sources in 30 seconds and start asking questions immediately. No semantic layer, no training, no IT tickets. The 82/100 BUA score reflects true independence. Users investigate complex questions through natural conversation, just like working with a human analyst.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Power BI Copilot work with Excel?</h3>
<p class="content-section__paragraph">Power BI Copilot requires exporting data from Power BI to Excel manually. No native Excel integration exists. Users must switch contexts, losing investigation flow. Scoop works directly inside Excel, letting users analyze data where they're already working, maintaining context and productivity.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">What's the typical implementation time for Tellius?</h3>
<p class="content-section__paragraph">Tellius implementation typically takes 3-6 months including data integration, model training, and user setup. The low 22/100 BUA score reflects this complexity. Organizations need consultants for initial setup and ongoing maintenance. Compare to Scoop's 30-second connection and immediate value delivery.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">How is Scoop different from traditional BI tools?</h3>
<p class="content-section__paragraph">Scoop is an AI analyst you chat with, not a dashboard platform. Traditional BI like Power BI and Tellius require building reports first, then asking questions. Scoop starts with questions, automatically running multiple queries to find answers. It's investigation-first, not dashboard-first.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Why doesn't Scoop require training?</h3>
<p class="content-section__paragraph">Scoop uses natural language like ChatGPT—if you can type a question, you can use Scoop. No semantic layers, no query languages, no report building. The AI understands context and intent automatically. Business users become productive immediately, unlike traditional BI requiring weeks of training.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">How many queries does Power BI Copilot run to answer why questions?</h3>
<p class="content-section__paragraph">Power BI Copilot runs just one query per question, limited to existing report context. It can't chain queries for investigation. Finding root causes requires manually asking follow-up questions if the data model supports them. True investigation needs 3-10 connected queries, which Copilot can't perform.</p>
</div>
</div>
</section>
<section class="cta-section">
<div class="cta-section__title">See Scoop in Action</div>
<div class="cta-section__subtitle">
Join 500+ companies using Scoop to democratize data investigation
</div>
<a href="https://www.scoopanalytics.com/book-demo" class="btn--primary">Book Your Demo</a>
</section>
