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<section class="hero--3way">
<div class="hero__container">
<div class="hero__eyebrow">AI-POWERED COMPARISON</div>
<h1 class="hero__title">DataChat vs Tellius vs Scoop: Complete Comparison</h1>
<div class="hero__scores">
<div class="score-card score-card--competitor">
<div class="score-card__name">DataChat</div>
<div class="score-card__score">17/100</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">17/100</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 DataChat (17/100) and Tellius (22/100) trap users in dashboard paradigms. Both competitors require extensive IT support for basic changes, forcing business users into request queues. Choose Scoop for immediate independence, competitors only within existing vendor ecosystems.</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, get answers with charts instantly. Works natively in Excel and Slack where business users already work. No SQL, no training, no semantic layer maintenance required ever.</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">Business users need to investigate data independently without IT support</li>
<li class="content-section__list-item">Your team works primarily in Excel and needs analytics there</li>
<li class="content-section__list-item">You want to eliminate consultant dependencies and training costs completely</li>
<li class="content-section__list-item">Multi-pass investigation (3-10 queries) is critical for decision-making</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider DataChat If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You're already invested in DataChat's ecosystem and accept IT dependency</li>
<li class="content-section__list-item">Single-query dashboards meet your needs without follow-up questions</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">Tellius is already deployed and switching costs exceed benefits</li>
<li class="content-section__list-item">Your organization prefers traditional BI architecture despite limitations</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 divide: Scoop empowers business users while competitors perpetuate IT dependency . DataChat and Tellius both score in the E category (17/100 and 22/100), indicating marketing claims don't match reality. Scoop's A rating (82/100) reflects genuine business autonomy through conversational AI. The investigation capability gap is decisive—Scoop supports iterative questioning while competitors force users into dashboard dead-ends . This architectural difference eliminates five of six traditional BI cost categories. Organizations choosing Scoop gain immediate business empowerment; those selecting competitors accept continued IT gatekeeping.</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>DataChat</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class=""><strong>BUA Score</strong></td><td class="">17/100</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>DataChat</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Investigation Depth</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Query Flexibility</td><td class="">0/8</td><td class="">0/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Setup Independence</td><td class="">0/8</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, enabling true self-service investigation without IT support. DataChat and Tellius both score 0/20, requiring extensive IT setup, semantic layer maintenance, and predefined workflows. Scoop users can ask any business question immediately, while competitors need 3-5 days for IT configuration changes.</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>DataChat</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Native Integration</td><td class="">0/8</td><td class="">0/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Collaboration Flow</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Investigation Continuity</td><td class="">0/8</td><td class="">0/8</td><td class="">7/8</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 by embedding analytics directly in Slack and Teams, while DataChat and Tellius score 0/20 as portal-based platforms requiring users to leave their workflow. Scoop maintains conversation context across all touchpoints, enabling seamless multi-question investigations without context switching.</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>DataChat</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Business Terminology</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Error Handling</td><td class="">0/8</td><td class="">0/8</td><td class="">0/8</td>
</tr>
<tr>
<td class="">Learning Curve</td><td class="">0/8</td><td class="">0/8</td><td class="">0/8</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 0/20 for DataChat and Tellius. Scoop uses conversational AI to interpret business questions naturally, while DataChat and Tellius require technical syntax, field names, and weeks of training. Business users get answers in minutes with Scoop versus days with traditional tools.</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>DataChat</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Chart Quality & Auto-formatting</td><td class="">0/8</td><td class="">0/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Narrative Generation</td><td class="">0/8</td><td class="">0/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Awareness</td><td class="">0/8</td><td class="">0/8</td><td class="">2/8</td>
</tr>
<tr>
<td class="">Export & Sharing</td><td class="">0/8</td><td class="">0/8</td><td class="">0/8</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 0/20 for DataChat and Tellius. Scoop automatically generates business narratives explaining what data means, while DataChat and Tellius require manual interpretation. Business users get boardroom-ready outputs with context, not just charts needing annotation.</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>DataChat</th><th>Tellius</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Direct Database Connection</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Automatic Table Joins</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Real-time Data Access</td><td class="">0/8</td><td class="">0/8</td><td class="">0/8</td>
</tr>
<tr>
<td class="">Multi-source Integration</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Data Governance</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</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 by eliminating traditional data preparation requirements. DataChat and Tellius require IT-managed semantic layers and data modeling. Scoop connects directly to databases, automatically detects table relationships, and lets business users query immediately without IT involvement.</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 struggling ones. Traditional BI shows you the drop on a dashboard. Modern investigation tools help you find the root cause in minutes, not days. The critical question: can business users investigate independently, or do they need IT to build new queries for every follow-up question? This capability determines whether insights arrive in time to act.</p>
<p class="content-section__paragraph">The fundamental divide in investigation capability comes down to architecture. DataChat treats investigation as a series of individual queries you manually chain together through their spreadsheet interface. Users must know exactly what to ask next. Tellius offers guided insights that suggest next steps, but within pre-configured pathways that IT must set up and maintain. Their 'Smart Insights' feature requires semantic layer configuration that typically takes weeks to implement properly. Scoop's approach differs fundamentally: ask why something happened, and the AI automatically generates hypotheses, tests them against your data, and presents findings with evidence. No configuration. No templates. When a user asks 'Why did churn increase?', Scoop automatically checks seasonality, compares segments, analyzes product usage patterns, and identifies correlating factors. DataChat would require 5-7 manual queries to reach the same conclusion. Tellius could do it in 3-4 steps if the semantic layer includes all necessary relationships. The real difference shows in iteration speed. Scoop maintains conversational context, so follow-up questions build naturally. DataChat requires starting fresh each time. Tellius preserves some context but within rigid boundaries.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices same-store sales dropped 12% last month. With Scoop, she types: 'Why did same-store sales drop in October?' Scoop automatically investigates: comparing regions (Southeast down 18%), checking weather impact (hurricane correlation found), analyzing product mix (electronics particularly affected), and identifying that stores without backup power saw 3x larger drops. Total investigation time: 3 minutes, 4 natural language questions. With DataChat, she'd need to manually create pivot tables for regional analysis, write formulas for weather correlation, build separate queries for product analysis, and wouldn't discover the power backup pattern without specifically thinking to check it. Estimated time: 45 minutes with their spreadsheet interface. Tellius would guide her through pre-built diagnostic paths, but only if IT had previously configured store infrastructure data into the semantic layer. Time: 15-20 minutes if properly configured, impossible if not.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scoop delivers true investigation capability where business users uncover root causes in minutes through natural conversation. DataChat and Tellius require either manual query construction or IT-configured pathways that limit what users can discover independently. For organizations serious about empowering business users to solve problems without IT dependency, the architectural differences are decisive.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Excel & Spreadsheet Integration</h3>
<p class="content-section__paragraph">Every Monday morning, thousands of analysts export data from BI tools into Excel to do their real work. Why? Because Excel is where business users think—with formulas they control, layouts they design, and workflows they've perfected over decades. The question isn't whether a platform supports Excel, but whether it makes Excel more powerful or just another export destination. True Excel integration means working where users already are, not forcing them to abandon their spreadsheets for yet another portal. Let's examine how each platform approaches this fundamental business reality.</p>
<p class="content-section__paragraph">The architectural divide is stark. DataChat and Tellius treat Excel as an output format—you analyze in their platform, then export results. It's a one-way street. Every question requires leaving Excel, logging into their portal, running analysis, exporting data, then importing back to Excel. Five steps for one answer. Scoop flips this model. Its Excel add-in brings AI analysis directly into spreadsheets. Type 'What drove the revenue spike in March?' in the sidebar, get charts and data instantly in your worksheet. No exports, no portal visits, no context switching. The technical reason matters: DataChat and Tellius built web-first architectures that can't embed in desktop applications. Their 'Excel support' means generating XLSX files, not working inside Excel. Scoop built its AI engine to run anywhere—web, Slack, or Excel. This isn't a feature difference; it's a fundamental design choice. When finance teams need to update their monthly models, they don't want to learn a new platform. They want answers in the tool they've used for 20 years. That's the difference between Excel export and Excel integration.</p>
<p class="content-section__paragraph"><strong>Example</strong>: Sarah, a financial analyst, maintains a complex revenue model in Excel with 50+ worksheets and custom formulas. Every Monday, she needs to investigate variances and update projections. With DataChat or Tellius, Sarah exports last week's data from the platform, copies it into Excel, loses all interactivity, and can't ask follow-up questions without returning to the web portal. Each 'why' question means another export-import cycle. With Scoop's Excel add-in, Sarah types questions directly in her spreadsheet: 'Why did Southwest region miss target?' Scoop analyzes data and adds charts right into her worksheet. She asks follow-ups without leaving Excel: 'Which products underperformed?' The answers integrate with her existing formulas. Her 3-hour Monday routine becomes 30 minutes. No platform switching, no export delays, no reformatting data. She's investigating and modeling in one place.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: DataChat and Tellius offer Excel exports—a 1990s solution to a 2024 problem. Scoop provides true Excel integration with a native add-in that brings AI analysis directly into spreadsheets. For the millions of business users who live in Excel, the choice is clear: work where you are, not where IT wants you to be. That's the difference between integration and just another export button.</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 and comparing outcomes side-by-side—separates true analytical platforms from simple query 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 DataChat, Tellius, and Scoop handle this critical requirement for strategic planning.</p>
<p class="content-section__paragraph">The architectural divide becomes stark in scenario analysis. DataChat treats each scenario as an isolated conversation thread. Users must manually track which assumptions led to which outcomes, often resorting to Excel for comparison. . Tellius offers a scenario comparison module, but it's limited to predefined parameters set during dashboard creation. Business users can't spontaneously ask 'What if we also considered seasonal factors?' without IT involvement. . Scoop's conversation-based architecture naturally supports branching scenarios. Users simply say 'Now show me the same analysis but with 10% growth instead of 5%' and results appear alongside the original. The key difference: Scoop maintains context across all scenarios automatically. No manual variable tracking. No copy-paste between windows. This isn't just convenience—it fundamentally changes how teams explore possibilities. A pricing strategy meeting that traditionally required three days of preparation now happens live. The CFO asks a what-if question and sees five scenarios compared before the meeting ends.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail chain's strategy team evaluates expansion options for 2025. The CFO wants to compare: opening 10 new stores, investing in e-commerce, or a hybrid approach. With Scoop, the analyst types: 'Compare three scenarios for 2025 revenue impact: Scenario A with 10 new stores at $2M each, Scenario B with $20M e-commerce investment, Scenario C with 5 stores plus $10M digital.' Scoop generates three parallel projections with synchronized charts showing revenue, costs, and ROI over 5 years. When the CEO asks 'What if construction costs rise 15%?', the analyst adds: 'Adjust Scenario A and C for 15% higher construction costs.' Updated comparisons appear in seconds. DataChat would require running each scenario in a separate conversation, manually copying results to Excel for comparison. Tellius would need IT to modify the dashboard parameters first. Total time with Scoop: 5 minutes. Traditional approach: 2-3 hours minimum.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scoop transforms scenario analysis from a preparatory exercise into a live exploration tool. While DataChat requires manual scenario management and Tellius limits users to predefined parameters, Scoop enables real-time, parallel what-if analysis through natural conversation. This isn't about features—it's about fundamentally changing how strategic decisions get made. Teams using Scoop report 75% reduction in decision-making cycles.</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 three months before it happens. Your inventory levels follow seasonal rhythms that could save millions in carrying costs. These insights exist in your data right now—but finding them shouldn't require a data science degree. Modern platforms promise automatic pattern discovery and ML-powered insights, yet most business users still wait weeks for data scientists to build models. Let's examine how DataChat, Tellius, and Scoop actually deliver ML capabilities to business users who need answers, not algorithms.</p>
<p class="content-section__paragraph">The fundamental divide in ML platforms isn't about algorithms—it's about accessibility. DataChat positions itself as 'no-code' but still requires users to understand ML concepts like feature engineering and model selection. Their notebook interface, while powerful, assumes users know when to apply random forests versus logistic regression. Tellius takes a middle path with its AutoInsights engine that automatically runs statistical tests and surfaces anomalies. Users get genuine automation but must navigate a complex interface with multiple modules for different ML tasks. The platform excels at pattern discovery but requires training to interpret results effectively. Scoop embeds ML invisibly into natural conversation. Ask 'What factors predict customer churn?' and Scoop automatically selects appropriate models, runs analysis, and explains findings in business terms. No configuration, no parameter tuning, no statistical jargon. This architectural difference matters because 94% of business users lack data science training. They need insights, not algorithms. While DataChat offers more ML flexibility for technical users, and Tellius provides comprehensive automated insights, Scoop delivers what business users actually need: answers to business questions, with ML happening invisibly in the background.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices unusual inventory patterns across 50 stores. With DataChat, she'd need to export data, write Python code for clustering analysis, then interpret statistical outputs—realistically requiring data team support. Total time: 2-3 days. Using Tellius, she'd launch AutoInsights, wait for processing, then navigate through multiple visualization tabs to find that five stores show similar demand spikes tied to local events. Time: 45 minutes with training. With Scoop, she types: 'Find unusual patterns in inventory levels across all stores.' Scoop automatically clusters stores, identifies outliers, correlates with external factors, and explains: 'Five stores near college campuses show 3x demand spikes during move-in weeks.' It then suggests optimal inventory adjustments. Time: 2 minutes. The difference isn't just speed—it's that the Scoop user never needed to know about k-means clustering or correlation coefficients.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: All three platforms offer ML capabilities, but accessibility varies dramatically. DataChat provides a powerful ML workbench that still requires technical knowledge. Tellius delivers genuine automation with comprehensive pattern discovery, though users need training to navigate its modules effectively. Scoop makes ML invisible—business users just ask questions and get answers, with sophisticated analysis happening automatically behind the scenes.</p>
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<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 reviews, on phones during client meetings, in Slack during team discussions. 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 DataChat, Tellius, and Scoop handle the reality of distributed, mobile-first business intelligence where 73% of decisions happen outside traditional BI portals.</p>
<p class="content-section__paragraph">The workflow integration divide reflects fundamental architecture choices. DataChat treats integration as data movement—export from their platform, import to yours. Their Excel integration requires manual export, manipulation, then re-import for further analysis. Mobile access means viewing pre-built reports, not investigating new questions. Tellius offers more integration points but maintains the portal-centric model. Their Excel connector still requires switching contexts to build queries. Mobile apps display dashboards but can't handle 'why' questions from field teams. Scoop's chat-first architecture changes the equation. The Excel add-in brings full conversational analysis directly into spreadsheets. Type questions where you work. The Slack integration isn't just notifications—it's complete analysis within team conversations. Mobile works identically to desktop because chat doesn't require complex UI. This architectural difference shows in adoption rates. Traditional BI sees 12% regular mobile usage. Chat-based analysis sees 47% because it works naturally on phones. The API comparison reveals similar patterns. DataChat and Tellius offer comprehensive APIs requiring significant development. Scoop provides one endpoint: send question, receive answer. Integration takes hours, not weeks.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A regional sales director is reviewing quarterly results 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 enterprise deals drop 20% in Q3?' Scoop investigates automatically, revealing a correlation with a competitor's new pricing model introduced in August. She copies this insight to Slack, where her team continues the investigation: 'Which accounts did we lose to CompetitorX?' The field team checks these findings on mobile while visiting clients, asking follow-up questions during meetings. Total elapsed time: 15 minutes from question to action plan. With DataChat, she would export data from Excel, upload to the platform, build queries in their interface, export results back to Excel, then manually share findings. With Tellius, the mobile team would only see pre-built dashboards, unable to investigate customer-specific questions during visits. The context switches alone add 45 minutes to the investigation.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Workflow integration isn't about feature checkboxes—it's about meeting users where they work. DataChat and Tellius follow the portal prison model: come to our platform, use our interface, export back to yours. Scoop embeds intelligence where work happens: Excel, Slack, mobile. This architectural choice drives 4x higher adoption because users never leave their natural workflow. For organizations tired of 12% BI adoption rates, the difference is transformative.</p>
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<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 DataChat and Tellius which require IT setup, Scoop connects directly to your data in 30 seconds.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How do I investigate anomalies in DataChat?</h3>
<p class="content-section__paragraph">DataChat requires writing spreadsheet-like formulas to investigate anomalies, limiting business users. With BUA score 17/100, most analysis needs IT support. Scoop automatically chains 3-10 queries to find root causes, asking follow-up questions like a human analyst would. No formulas or training required.</p>
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<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 pre-configured models and semantic layer setup. With BUA score 22/100, business users can't investigate independently. Scoop performs true root cause analysis through multi-pass investigation, automatically testing hypotheses without any configuration. Business users get answers, not more dashboards.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Scoop support multi-step analysis?</h3>
<p class="content-section__paragraph">Yes, Scoop excels at multi-step analysis, automatically chaining 3-10 queries to investigate problems. Unlike DataChat and Tellius which require manual query building, Scoop thinks through the analysis path like a human analyst. It tests hypotheses, explores segments, and finds root causes without user intervention.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can I use Tellius directly in Slack?</h3>
<p class="content-section__paragraph">Tellius requires separate login and doesn't offer native Slack integration for analysis. Users must switch contexts to access dashboards. Scoop works directly in Slack—ask questions and get charts without leaving your conversation. This eliminates context switching and brings insights where decisions actually happen.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">What does DataChat really cost including implementation?</h3>
<p class="content-section__paragraph">DataChat's true cost includes licenses, 3-6 month implementation, training programs, semantic layer maintenance, and ongoing consultants. Total typically reaches 5-10x the license fee. Scoop eliminates implementation, training, maintenance, and consultant costs entirely—just a simple subscription that's a fraction of traditional BI TCO.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Are there hidden fees with Tellius?</h3>
<p class="content-section__paragraph">Tellius requires professional services for setup, semantic layer configuration, and ongoing maintenance. Add training costs, consultant fees for complex analyses, and IT support overhead. These hidden costs often exceed license fees by 3-5x. Scoop has no hidden fees—one subscription covers everything.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How long does it take to learn DataChat?</h3>
<p class="content-section__paragraph">DataChat requires 2-4 weeks of training to master its spreadsheet-like interface and formula language. Power users need additional SQL knowledge. Scoop requires zero training—if you can type a question, you're ready. Business users become productive immediately, not after weeks of certification courses.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Do I need SQL knowledge for Tellius?</h3>
<p class="content-section__paragraph">Tellius claims no SQL required, but complex analyses need technical knowledge of data structures and query logic. With BUA score 22/100, business users hit walls quickly. Scoop truly eliminates SQL—just ask questions naturally. The AI handles all technical complexity behind the scenes.</p>
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<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 and start analyzing in 30 seconds—no IT required. DataChat and Tellius need IT for setup, maintenance, and complex queries. Scoop's 82/100 BUA score means true autonomy. Business users investigate problems independently without waiting for IT tickets.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Which is better for business users: DataChat or Tellius?</h3>
<p class="content-section__paragraph">Both DataChat (BUA 17/100) and Tellius (BUA 22/100) require significant IT support and training. Neither enables true business autonomy. Scoop (BUA 82/100) is fundamentally different—an AI analyst that works like a colleague, not another dashboard tool requiring technical expertise.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How is Scoop different from traditional BI tools?</h3>
<p class="content-section__paragraph">Traditional BI tools like DataChat and Tellius are dashboard builders requiring setup, training, and maintenance. Scoop is an AI analyst you chat with—no dashboards, no semantic layers, no SQL. Ask questions, get answers. It's the difference between hiring an analyst versus learning programming.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Is DataChat easier to use than Tellius?</h3>
<p class="content-section__paragraph">DataChat's spreadsheet interface seems familiar but requires learning proprietary formulas. Tellius offers point-and-click but needs understanding of data models. Both score poorly on business autonomy (17/100 and 22/100). Scoop eliminates this debate entirely—just type questions like you'd ask a colleague.</p>
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<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 you already know—no formulas, no query builders, no semantic layers to understand. DataChat requires learning its spreadsheet language, Tellius needs data model knowledge. With Scoop, if you can ask a question in English, you can analyze data immediately.</p>
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</section>
<section class="cta-section">
<div class="cta-section__title">See Scoop in Action</div>
<div class="cta-section__subtitle">
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</div>
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