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<section class="hero--3way">
<div class="hero__container">
<div class="hero__eyebrow">AI-POWERED COMPARISON</div>
<h1 class="hero__title">Qlik Sense vs Snowflake Cortex vs Scoop: Complete Comparison</h1>
<div class="hero__scores">
<div class="score-card score-card--competitor">
<div class="score-card__name">Qlik Sense</div>
<div class="score-card__score">47/100</div>
<div class="score-card__label">BUA Score</div>
</div>
<div class="score-card score-card--competitor">
<div class="score-card__name">Snowflake Cortex</div>
<div class="score-card__score">47/100</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 Qlik Sense (47/100) and Snowflake Cortex (26/100) trap users in dashboards. Both competitors require IT support for anything beyond pre-built views, blocking the iterative questioning business users need. Choose Scoop for immediate independence, competitors only if already invested in their 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 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">Business users need to investigate data independently without waiting for IT</li>
<li class="content-section__list-item">Your team lives in Excel and needs analytics without leaving spreadsheets</li>
<li class="content-section__list-item">You want to eliminate consultant dependencies and training costs permanently</li>
<li class="content-section__list-item">Real-time investigation matters more than pretty static dashboards</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Qlik Sense If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You're already heavily invested in the Qlik ecosystem and can't migrate</li>
<li class="content-section__list-item">Static dashboards meet your needs and users don't require investigation capabilities</li>
<li class="content-section__list-item">You have dedicated IT resources to maintain semantic layers continuously</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Snowflake Cortex If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">Your data lives exclusively in Snowflake and you need native integration</li>
<li class="content-section__list-item">You have data engineers available to write and maintain SQL queries</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 the truth: Scoop's 82/100 demonstrates genuine business empowerment while Qlik Sense (47/100) and Snowflake Cortex (26/100) perpetuate IT dependency . Business users gain immediate independence to investigate data themselves, transforming how organizations make decisions.</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>Qlik Sense</th><th>Snowflake Cortex</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class=""><strong>BUA Score</strong></td><td class="">47/100</td><td class="">26/100</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>Qlik Sense</th><th>Snowflake Cortex</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Investigation Capability</td><td class="">2/8</td><td class="">3/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Setup Requirements</td><td class="">1/8</td><td class="">2/8</td><td class="">5/8</td>
</tr>
<tr>
<td class="">Query Modification</td><td class="">0/8</td><td class="">1/8</td><td class="">5/8</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 by enabling full investigation through conversation, while Qlik Sense and Snowflake Cortex score 3/20 and 6/20 respectively, requiring IT support for setup and modifications. Business users can ask Scoop follow-up questions naturally without SQL knowledge or dashboard editing permissions.</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>Qlik Sense</th><th>Snowflake Cortex</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Workflow Integration</td><td class="">1/8</td><td class="">2/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">0/8</td><td class="">1/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Multi-step Investigation</td><td class="">0/8</td><td class="">2/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Response Delivery</td><td class="">0/8</td><td class="">1/8</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 living in Slack/Teams, while Qlik Sense and Snowflake Cortex score 0/20, forcing users into separate portals. Scoop maintains conversation context for natural follow-ups. Traditional BI platforms require leaving your workflow, losing context with every question.</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>Qlik Sense</th><th>Snowflake Cortex</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Business Terminology Support</td><td class="">1/8</td><td class="">2/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Error Recovery & Guidance</td><td class="">0/8</td><td class="">1/8</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 16/20 on Understanding by using AI to interpret business questions without semantic layer setup. Qlik Sense and Snowflake Cortex require IT teams to pre-map every business term, creating 2-3 week delays for new metrics. Scoop understands context automatically while competitors force users to learn database terminology.</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>Qlik Sense</th><th>Snowflake Cortex</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Output Format Flexibility</td><td class="">2/8</td><td class="">1/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Context-Aware Formatting</td><td class="">0/8</td><td class="">0/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Business Language Translation</td><td class="">1/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Live vs Static Output</td><td class="">3/8</td><td class="">2/8</td><td class="">5/8</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 unscored Qlik Sense and Snowflake Cortex. Scoop automatically formats answers with business language and context-appropriate charts. Qlik Sense requires manual screenshot exports and PowerPoint formatting. Snowflake Cortex returns raw SQL results needing significant formatting work.</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>Qlik Sense</th><th>Snowflake Cortex</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Direct Database Connection</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Real-time Data Access</td><td class="">1/8</td><td class="">2/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Multi-source Integration</td><td class="">2/8</td><td class="">1/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Data Governance</td><td class="">3/8</td><td class="">4/8</td><td class="">5/8</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 semantic layers entirely. Qlik Sense and Snowflake Cortex require IT-maintained translation layers between databases and business users, creating inconsistencies. Scoop connects directly to raw data via natural language, providing real-time access without technical knowledge or interpretation conflicts.</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 can save millions. Traditional BI shows you the drop on a dashboard. Investigation platforms help you find the root cause through iterative questioning—was it pricing, competition, or market conditions? This capability separates reporting tools from true analytical partners. The key metric: how many queries does it take to get from symptom to root cause? Most platforms require 5-10 manual steps. The best enable fluid investigation in 3-4 natural questions.</p>
<p class="content-section__paragraph">The architectural divide is stark. Qlik Sense uses an associative model—powerful for exploration but requiring users to understand data relationships and manually navigate. You click through dimensions hoping to spot patterns. Snowflake Cortex treats each question as isolated SQL generation. Ask about revenue drops, get a number. Want to know why? Write another query from scratch. No memory, no context, no automatic investigation. Scoop operates like a data analyst conducting an investigation. Ask about the revenue drop and it automatically checks seasonality, segments, and correlations. Follow up with 'what about competitor pricing?' and it maintains context, building on previous findings. This conversational threading means business users can pursue hunches naturally. Where Qlik requires 8-10 clicks through associations and Cortex needs 5-6 separate SQL queries, Scoop typically reaches root cause in 3-4 conversational exchanges. The difference: 30 minutes versus 5 minutes to answer 'why.'</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager sees same-store sales dropped 12% last month. In Qlik Sense, she opens the sales dashboard, clicks through store dimensions, manually filters time periods, checks various metrics, and builds mental hypotheses about patterns—taking 25 minutes to identify that three stores near a new competitor underperformed. With Snowflake Cortex, she'd need to write SQL: first for the overall drop, then by store, then by geography, then correlating with competitor locations—if she even knows to check that. With Scoop, she types: 'Why did same-store sales drop last month?' Scoop automatically investigates: checks all stores, identifies the three outliers, correlates with local market data, and surfaces the new competitor connection. She follows up: 'What products are most affected?' Total time: 4 minutes. No SQL, no clicking through dimensions—just answers.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Investigation capability isn't about having data—it's about finding answers quickly. Qlik Sense offers exploration through clicking and filtering, requiring users to know where to look. Snowflake Cortex generates SQL for individual questions but can't connect the dots. Scoop conducts actual investigations, automatically testing hypotheses and maintaining context across questions. For business users needing root cause analysis, the difference is between being handed a map (Qlik), a compass (Cortex), or having a guide who knows the terrain (Scoop).</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-used business intelligence tool, with 750 million users who already know how to use it. The real question isn't whether platforms connect to Excel—it's how seamlessly business users can leverage their existing Excel workflows while gaining modern analytics capabilities. This comparison examines whether platforms enhance Excel or force users to abandon it, focusing on the friction between familiar spreadsheet work and advanced analytics needs.</p>
<p class="content-section__paragraph">The architectural divide is stark. Qlik Sense offers an Excel add-in but requires users to understand Qlik's expression syntax and data model. You're essentially using Qlik through Excel, not enhancing Excel itself. Snowflake Cortex treats Excel as an export destination—users must write SQL queries in Snowflake, then manually export results. There's no live connection or formula integration. Scoop takes a fundamentally different approach: it enhances Excel rather than replacing it. Users type questions in plain English directly in Excel cells using =SCOOP() formulas. The AI understands context from surrounding data and returns live results that update automatically. Most critically, Scoop works with existing spreadsheets. That complex financial model you've refined for five years? Scoop enhances it without requiring a rebuild. This preserves institutional knowledge embedded in formulas, layouts, and workflows. For the 750 million Excel users worldwide, the difference is between learning a new platform (Qlik/Snowflake) versus gaining superpowers in the tool they already know.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A financial analyst maintains a complex monthly reporting spreadsheet with 15 tabs of calculations. She needs to add competitive analysis. With Scoop, she types =SCOOP("Compare our revenue growth to top 3 competitors last 6 months") in a cell. Results appear instantly, updating each month. She can drill down with =SCOOP("Why did Competitor A grow faster in Q3?") in the next cell. Total setup: 2 minutes. With Qlik Sense, she'd need IT to configure the data connection, learn Qlik expression syntax, and rebuild her report structure in Qlik's format. With Snowflake Cortex, she'd write SQL queries in Snowflake's console, export results, then manually paste into Excel—repeating monthly. The Scoop approach preserves her existing work while adding AI-powered analysis. The others require abandoning Excel workflows entirely.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scoop transforms Excel into an AI-powered analytics platform while preserving everything users already know. Qlik and Snowflake treat Excel as either a limited viewer (Qlik) or export destination (Snowflake), forcing users to learn new tools and rebuild existing work. For organizations with thousands of critical Excel files, Scoop's enhancement approach delivers immediate value without disruption.</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 10% versus cutting costs 5%?', they need to see multiple scenarios simultaneously, not sequentially. This capability—comparing different futures side-by-side—separates strategic planning tools from basic reporting. Most BI platforms force users to run scenarios one at a time, export to Excel, then manually compare. True scenario analysis means seeing multiple what-ifs on one screen, with automatic variance calculations and impact assessments. Let's examine how each platform handles this critical strategic planning need.</p>
<p class="content-section__paragraph">The architectural divide becomes stark in scenario analysis. Qlik Sense treats each scenario as a separate analysis path. Users build one view, screenshot it, adjust parameters, build another view, screenshot again, then compare manually in PowerPoint. This serial processing means a typical three-scenario comparison takes 45-60 minutes. Snowflake Cortex requires writing UNION queries to combine scenarios, with manual CASE statements for variance calculations. Business users can't do this alone—they need data team support for every comparison. Scoop's conversational architecture enables true parallel processing. Users type 'Compare revenue impact of 10% price increase versus 20% volume growth versus 15% cost reduction.' Scoop generates all three scenarios simultaneously, calculates variances automatically, and presents them side-by-side with impact rankings. The conversation history preserves all assumptions, creating natural documentation. When executives ask follow-up questions like 'What if we combine the first two scenarios?', Scoop builds on existing analysis rather than starting over. This investigation-first design means scenario planning happens in minutes, not hours.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A CFO preparing for board meeting needs to present three budget scenarios: aggressive growth, steady state, and recession planning. With Scoop, she types: 'Compare three scenarios for 2025: Scenario A with 20% revenue growth and 15% hiring, Scenario B with 5% growth and flat hiring, Scenario C with -10% revenue and 20% cost cuts.' Scoop instantly generates a side-by-side comparison showing revenue, costs, EBITDA, and cash flow for all three scenarios, with variance percentages between each. She asks: 'What's the break-even point for each scenario?' and gets the analysis in seconds. Total time: 5 minutes. In Qlik Sense, she would need to create three separate apps with different parameter settings, manually calculate variances in Excel, and build the comparison visualization from scratch. Time required: 2-3 hours minimum, likely requiring analyst support.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Side-by-side scenario analysis reveals the fundamental limitation of dashboard-centric platforms: they're built for single views, not comparative analysis. While Qlik Sense and Snowflake Cortex force sequential scenario building with manual comparison, Scoop's conversational approach enables true parallel analysis in minutes. For strategic planning where multiple futures must be evaluated simultaneously, the difference between 5 minutes and 3 hours isn't just efficiency—it's the difference between dynamic planning sessions and static presentations.</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 each platform actually delivers ML capabilities to the people who need them: business users making daily decisions.</p>
<p class="content-section__paragraph">The fundamental divide in ML capabilities isn't about algorithms—it's about accessibility. Qlik Sense bundles ML features in its Insight Advisor, but business users can't actually trigger custom analysis. They see pre-configured insights that IT sets up. Want to find correlations in a new dataset? Submit a ticket. Snowflake Cortex offers powerful ML functions like ANOMALY_DETECTION and FORECAST, but they're locked behind SQL. A sales manager investigating revenue patterns needs to write: SELECT ANOMALY_DETECTION(revenue, timestamp) FROM sales_data. That's not happening without IT help. Scoop takes a different approach. When you ask 'What's driving customer churn?', it automatically runs correlation analysis, identifies patterns, and surfaces predictive indicators. No configuration. No SQL. The ML happens invisibly while you investigate. This architectural difference matters because 87% of business questions benefit from pattern detection, but only 12% of companies have enough data scientists to help. Traditional platforms built ML for data scientists. Scoop built it for everyone else.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices inventory costs spiking. With Scoop, she types: 'What patterns explain our inventory costs?' Scoop automatically analyzes seasonality, correlates with sales patterns, identifies anomalous SKUs, and discovers that slow-moving items from a specific supplier have 3x higher carrying costs. It suggests optimal reorder points based on detected patterns. Total time: 4 minutes, zero configuration. In Qlik Sense, she'd need IT to configure Insight Advisor rules for inventory analysis—a 2-week project. The patterns exist but remain invisible to business users. With Snowflake Cortex, a data analyst would write multiple SQL queries using CORRELATION and ANOMALY_DETECTION functions, test different parameters, and build visualizations. Even with skilled resources available immediately, it's a 2-day investigation minimum.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Machine learning shouldn't require a PhD to use. While Qlik Sense locks ML behind IT configuration and Snowflake Cortex requires SQL expertise, Scoop makes pattern discovery as simple as asking a question. Business users get automatic anomaly detection, correlation analysis, and predictive insights without writing code or waiting for IT. That's the difference between ML as a feature checkbox and ML as a daily business tool.</p>
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<h3 class="content-section__subtitle">Workflow Integration & Mobile</h3>
<p class="content-section__paragraph">Your best insights are worthless if they're trapped in a browser tab. Modern data work happens where business happens—in Excel during budget planning, in Slack during team discussions, on phones during client visits. The real test isn't whether a platform has mobile apps or APIs. It's whether business users can actually get answers without leaving their workflow. Let's examine how each platform handles this critical requirement for business agility.</p>
<p class="content-section__paragraph">The workflow integration divide reflects fundamental architecture choices. Qlik Sense treats integration as an afterthought—you can export data or embed dashboards, but you can't actually work with data outside their portal. Their mobile app displays pre-built dashboards without investigation capability. Snowflake Cortex has no workflow integration at all; it's SQL-only access requiring technical users to bridge any workflow gaps. Scoop's chat-based architecture enables native integration everywhere. The Excel add-in brings full conversation capability into spreadsheets. Slack integration means teams investigate together without context switching. Mobile web access provides complete functionality, not dumbed-down viewers. This isn't about having more integrations—it's about maintaining full analytical power wherever users work. Traditional BI platforms built portal prisons that force users to leave their workflow. Scoop brings the analyst to where work happens. The difference shows in adoption: users actually use tools that meet them where they are.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A regional 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 are Southeast bookings down 30% this month?' Scoop analyzes the data, identifies three underperforming territories, and shows that a key account manager left two weeks ago. She shares findings in Slack where her team discusses coverage plans. Total elapsed time: 4 minutes, zero context switches. With Qlik Sense, she'd need to leave Excel, log into the portal, navigate to the right dashboard, apply filters, export data back to Excel, and manually share screenshots in Slack—assuming she has dashboard access. Snowflake Cortex would require writing SQL queries or waiting for an analyst. The workflow friction multiplies across hundreds of daily decisions.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Workflow integration isn't about feature checkboxes—it's about eliminating friction in daily work. Qlik Sense forces users into their portal. Snowflake Cortex offers no business user integration. Scoop meets users where they work with full analytical power intact. For organizations serious about data-driven decisions, the choice is between forcing behavior change or enabling existing workflows.</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 Qlik Sense and Snowflake Cortex which require IT setup, Scoop connects directly to your data in 30 seconds.</p>
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<h3 class="content-section__subtitle">Which is better for business users: Qlik Sense or Snowflake Cortex?</h3>
<p class="content-section__paragraph">Neither excels for business users. Qlik Sense scores 47/100 on business autonomy, Snowflake Cortex just 26/100. Both require IT support, training, and technical knowledge. Scoop at 82/100 lets business users work independently. For true self-service analytics, neither traditional option matches Scoop's natural language approach.</p>
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<h3 class="content-section__subtitle">How do I investigate anomalies in Qlik Sense?</h3>
<p class="content-section__paragraph">Qlik Sense requires building multiple dashboards or using set analysis expressions to investigate anomalies. You'll need IT help creating drill-down paths. Scoop automatically runs 3-10 queries to find root causes, while Qlik's single-query model forces manual exploration through pre-built visualizations that may miss the real issue.</p>
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<h3 class="content-section__subtitle">Can Snowflake Cortex do root cause analysis automatically?</h3>
<p class="content-section__paragraph">No, Snowflake Cortex can't perform automatic root cause analysis. It answers single SQL queries but doesn't chain investigations. With a 26/100 business autonomy score, users need data engineers to write complex queries. Scoop automatically tests multiple hypotheses through 3-10 query chains, finding causes that single-query tools miss.</p>
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<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 per investigation. Unlike Qlik Sense's dashboard paradigm or Snowflake Cortex's single queries, Scoop tests hypotheses iteratively like a human analyst would. Business users just ask why something happened—Scoop handles the complex investigation path automatically.</p>
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<h3 class="content-section__subtitle">What does Qlik Sense really cost including implementation?</h3>
<p class="content-section__paragraph">Qlik Sense true cost includes licenses, implementation (3-6 months), training, maintenance, consultants, and productivity loss. Total cost typically reaches 5-10x the license fee. A $50,000 license becomes $250,000-500,000 in year one. Scoop eliminates five of six cost categories, reducing TCO by 90%.</p>
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<h3 class="content-section__subtitle">Do I need SQL knowledge for Snowflake Cortex?</h3>
<p class="content-section__paragraph">Yes, Snowflake Cortex requires SQL knowledge for anything beyond basic queries. While it translates simple questions, complex analysis needs SQL expertise. With a 26/100 business autonomy score, most users rely on data teams. Scoop handles complex multi-table joins automatically—no SQL knowledge needed ever.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How long does it take to learn Qlik Sense?</h3>
<p class="content-section__paragraph">Qlik Sense requires 2-4 weeks of formal training plus months of practice. Users must learn data modeling, set analysis, and expression syntax. Even then, complex queries need IT support. Scoop requires zero training—if you can type a question, you're ready. Business users become productive immediately.</p>
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<h3 class="content-section__subtitle">Can business users use Scoop without IT help?</h3>
<p class="content-section__paragraph">Yes, business users work completely independently with Scoop. Connect in 30 seconds, ask questions in plain English, get answers with charts. No semantic layer, no SQL, no training. Unlike Qlik Sense (47/100 autonomy) or Snowflake Cortex (26/100), Scoop's 82/100 score means true self-service.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Qlik Sense work with Excel?</h3>
<p class="content-section__paragraph">Qlik Sense offers limited Excel integration through add-ins and exports, but requires switching between applications. Data flows one-way through manual exports. Scoop works natively inside Excel—ask questions directly in spreadsheets where business users already work. No context switching, no export-import cycles, just natural workflow integration.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">What's the typical implementation time for Snowflake Cortex?</h3>
<p class="content-section__paragraph">Snowflake Cortex implementation takes 3-6 months including data modeling, security setup, and semantic layer configuration. You'll need data engineers throughout. After implementation, each new data source requires weeks of integration. Scoop connects in 30 seconds and business users start analyzing immediately—no implementation project needed.</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">Scoop is an AI analyst you chat with, not a dashboard builder. While Qlik Sense and Snowflake Cortex require technical skills and IT support, Scoop understands plain English questions. It automatically investigates problems through multiple queries, finding insights that single-query dashboard tools miss entirely.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Do I need consultants to use Qlik Sense?</h3>
<p class="content-section__paragraph">Yes, most Qlik Sense deployments require consultants for implementation, data modeling, and dashboard creation. Companies typically spend 2-3x the license cost on consulting. Even after launch, complex changes need external help. Scoop eliminates consultant dependency—business users handle everything themselves from day one.</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 like ChatGPT—you already know how to use it. No query languages, no semantic layers, no dashboard design. Just type questions as you'd ask a colleague. Qlik Sense requires weeks of training, Snowflake Cortex needs SQL knowledge. Scoop's interface is truly intuitive.</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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