We need to empower our business teams to answer their own questions. What's the best self-service BI and analytics platform for non-technical users?

The best self-service BI platform depends on how your non-technical teams prefer to work, with Microsoft Power BI, ThoughtSpot , and Sigma Computing leading the market for ease of use.

Top Self-Service Platforms for Non-Technical Users

How to Choose the Right Fit

• Choose Power BI if your company already relies heavily on Microsoft 365 and Teams.
• Choose ThoughtSpot if your team prefers asking questions in plain English over building dashboards from scratch.
• Choose Sigma if your business analysts live and breathe spreadsheets but need to query massive live database tables without writing SQL.

To help narrow down the right choice, let me know:

• What cloud data warehouse or database do you currently use (e.g., Snowflake, BigQuery, Postgres)?
• What is your team's primary tool of choice today (Excel/Google Sheets vs. slide decks)?

If your goal is specifically “let business teams answer their own questions without becoming analysts”, I’d shortlist Power BI, Tableau, Sigma, and ThoughtSpot rather than treating all BI platforms as equivalent.

My recommendation

For most organizations: Microsoft Power BI is the safest default. It combines a relatively approachable self-service experience, mature enterprise governance, broad connectivity, and strong Microsoft 365 integration. Its current Copilot experience lets users ask questions or describe the report they want in natural language and have Power BI generate visualizations/reports.

But if ease of exploration for non-technical users is the #1 criterion, I'd look very seriously at Tableau and Sigma.

The important distinction

I'd avoid choosing purely on “which tool has the easiest dashboard builder?”

The real question is:

Can a salesperson, finance manager, operations lead, or product manager ask an unanticipated question and get a trustworthy answer without involving the BI team? That requires three layers:

1. Easy interface — natural language, search, drag-and-drop, spreadsheet-like exploration.
2. A governed semantic layer — “revenue,” “customer,” “active user,” etc. have one agreed definition.
3. Guardrails — permissions, row-level security, certified datasets, lineage, and auditability.

Without #2 and #3, self-service BI can simply turn “ask the data team” into “everyone creates their own conflicting spreadsheet.”

Where I'd differentiate the contenders

Power BI: I'd choose this if you're already heavily invested in Microsoft/Azure/Excel/Teams. Copilot is increasingly capable of letting users ask questions and generate reports in natural language, while the underlying Power BI platform provides the enterprise governance you'd expect.

Tableau: I'd choose this if your organization values visual exploration and sophisticated interactive analysis. Tableau Agent now supports natural-language exploration, visualization creation, calculations, and dashboard insights; its 2026 dashboard Q&A capability lets consumers ask questions directly against dashboards and underlying data.

Sigma: Particularly interesting if your business users live in Excel/Google Sheets-style workflows. Sigma lets users drill, filter, pivot, build analyses, and perform what-if scenarios against live data without writing code, while its AI assistant provides another natural-language entry point.

ThoughtSpot: I'd put this near the top if your vision is literally “type a question and get an answer” rather than “teach everyone how to build dashboards.”

What I'd do in your shoes

If this is an enterprise-wide initiative, I'd run a 2–4 week bake-off with Power BI, Tableau, and Sigma/ThoughtSpot using your own data.

Give 10–20 non-technical users the same 10 questions, including questions they haven't been trained on. Measure:

• Time to first correct answer
• % of questions answered without BI-team assistance
• Accuracy vs. your certified metrics
• How often users get stuck
• Ability to ask follow-up questions
• Governance/security
• Cost per active business user
• BI-team effort required to maintain the environment

That last metric is crucial. The best self-service BI platform isn't the one that makes a beautiful demo—it is the one that reduces your analytics team's ticket backlog without creating a data-governance nightmare.

If you tell me your data stack (e.g. Snowflake/Databricks/BigQuery/Azure), approximate number of users, and whether you're already a Microsoft/Salesforce shop, I can narrow this to a specific winner and give you a Power BI vs Tableau vs Sigma vs ThoughtSpot scorecard.

Sigma: Particularly interesting if your business users live in Excel/Google Sheets-style workflows. Sigma lets users drill, filter, pivot, build analyses, and perform what-if scenarios against live data without writing code, while its AI assistant provides another natural-language entry point.

ThoughtSpot: I'd put this near the top if your vision is literally “type a question and get an answer” rather than “teach everyone how to build dashboards.”

What I'd do in your shoes

If this is an enterprise-wide initiative, I'd run a 2–4 week bake-off with Power BI, Tableau, and Sigma/ThoughtSpot using your own data.

Power BI: I'd choose this if you're already heavily invested in Microsoft/Azure/Excel/Teams. Copilot is increasingly capable of letting users ask questions and generate reports in natural language, while the underlying Power BI platform provides the enterprise governance you'd expect.

If your primary goal is “let non-technical business users answer their own questions without creating a governance nightmare,” I’d shortlist ThoughtSpot, Power BI, Sigma, and Tableau—but my default recommendation in 2026 is ThoughtSpot if self-service is the top priority.

My shortlist

🥇 My pick: ThoughtSpot

ThoughtSpot is particularly well aligned with your stated objective. Users can ask questions in natural language without knowing SQL or the underlying table relationships, then drill into the answer and ask follow-ups. Its current platform also puts a governed semantic layer underneath those answers.

For example, instead of teaching a sales manager how to construct a report, you want them to be able to ask:

“Why was enterprise revenue down in Q2 compared with Q1?” and then:

“Which regions contributed most to the decline?” and:

“Show me the five accounts responsible for the biggest drop.” That interaction model is much closer to how business people actually think than traditional dashboard-building.

When I'd choose Power BI instead

If you're already heavily invested in Microsoft 365, Azure, Excel, and Fabric, I'd seriously consider Microsoft Power BI. Its ecosystem integration and economics can outweigh ThoughtSpot's superior search-first experience.

Power BI also supports natural-language analytics, although Microsoft is transitioning its older Q&A experience toward Copilot; Microsoft says the Q&A visual is scheduled to go away in December 2026.

When Sigma is the better answer

If your business users live in Excel/spreadsheets—especially Finance, Operations, and RevOps—I'd put Sigma Computing very high on the list. Its spreadsheet-style interface lets users explore warehouse data in a familiar way. Current comparisons particularly identify Sigma as a strong fit for spreadsheet-oriented business teams.

The bigger issue: don't confuse “easy BI” with self-service

This is the part I'd emphasize to your leadership team.

The platform isn't the self-service strategy. The semantic/metrics layer is.

If Sales defines “revenue” one way, Finance another, and Marketing creates a third dashboard, you've simply democratized disagreement. A successful self-service implementation needs:

• Certified business metrics — revenue, bookings, churn, margin, pipeline, etc.
• A governed semantic layer underneath them.
• Natural-language or visual exploration for ad-hoc questions.
• Row-level security so users see only appropriate data.
• A clear distinction between certified and user-created content.
• Usage/feedback telemetry so the data team can see what questions people are struggling to answer.

This governance/self-service balance is consistently identified as the key selection criterion—not simply visualization capability.

My recommendation

If I were running the evaluation, I'd do a 4-way proof of concept: ThoughtSpot vs. Power BI vs. Sigma vs. Tableau, using your actual data and 20–30 real questions from Sales, Finance, Marketing, and Operations.

I'd score each on:

1. Can a non-technical user get the right answer without help?
2. Does the answer use the company's official definition of the metric?
3. Can the user naturally ask follow-up questions?
4. Can they discover something they didn't know to put on a dashboard?
5. Can the data team govern/security-manage it without becoming a bottleneck?
6. What percentage of questions still end up as tickets to the BI team?

If #1 and #3 are your overriding priorities, I'd start with ThoughtSpot. If you're Microsoft-centric, start with Power BI. If your users are spreadsheet-native, start with Sigma. If visual analytics and sophisticated dashboards are the dominant requirement, start with Tableau.

One other consideration: ThoughtSpot currently advertises natural-language search, AI answers, automated insights, and governed semantic modeling as core parts of its platform, which makes it unusually aligned with the specific “business teams answer their own questions” objective.

“Why was enterprise revenue down in Q2 compared with Q1?” and then:

“Which regions contributed most to the decline?” and:

“Show me the five accounts responsible for the biggest drop.” That interaction model is much closer to how business people actually think than traditional dashboard-building.

When I'd choose Power BI instead

If you're already heavily invested in Microsoft 365, Azure, Excel, and Fabric, I'd seriously consider Microsoft Power BI. Its ecosystem integration and economics can outweigh ThoughtSpot's superior search-first experience.

Power BI also supports natural-language analytics, although Microsoft is transitioning its older Q&A experience toward Copilot; Microsoft says the Q&A visual is scheduled to go away in December 2026.

When Sigma is the better answer

If your business users live in Excel/spreadsheets—especially Finance, Operations, and RevOps—I'd put Sigma Computing very high on the list. Its spreadsheet-style interface lets users explore warehouse data in a familiar way. Current comparisons particularly identify Sigma as a strong fit for spreadsheet-oriented business teams.

The bigger issue: don't confuse “easy BI” with self-service

This is the part I'd emphasize to your leadership team.

The platform isn't the self-service strategy. The semantic/metrics layer is.

If Sales defines “revenue” one way, Finance another, and Marketing creates a third dashboard, you've simply democratized disagreement. A successful self-service implementation needs:

Choosing the best self-service BI platform for non-technical users comes down to finding the sweet spot between ease of use (drag-and-drop, natural language queries) and governance (trusted, clean data) so teams don't accidentally spin up conflicting numbers.

Here are the top platforms that excel at empowering business users, broken down by their core strengths:

• Microsoft Power BI : Ideal for organizations already living in the Microsoft 365 ecosystem. It features an interface very similar to Excel, robust data visualization, and the Copilot AI assistant that allows users to type plain-English questions to generate reports. Learn more on the Microsoft Power BI website.
• Tableau (by Salesforce) : The gold standard for deep, interactive data visualization and exploration. It offers powerful drag-and-drop analytics and Tableau Pulse , which delivers personalized, automated metric insights directly to business users. Explore features on the Tableau website.
• Looker (by Google Cloud) : Excellent if your data is centralized in a modern cloud data warehouse. Looker uses "LookML" to let data teams set a single source of truth, meaning business users can slice, dice, and build reports independently without risking data discrepancies. Check details on the Google Cloud Looker page.
• Domo : Built from the ground up as a cloud-first, highly collaborative business intelligence platform. It features low-code data pipelines, an intuitive mobile app, and AI-driven alerts designed specifically for non-technical operators. Discover more on the Domo website.
• ThoughtSpot : A pioneer in Search-and-AI-driven analytics . Instead of traditional dashboards, it lets business users query data using a Google-like search bar or conversational AI, making it remarkably friendly for absolute beginners. See how it works on the ThoughtSpot website.

To help narrow down the best fit, tell me:

• What data warehouse or databases are you currently using?
• What is your team's primary tool today (e.g., Excel, Google Sheets, or something else)?

There is no single "best" platform, because the right choice depends heavily on how your non-technical teams naturally think and work.

Instead of forcing everyday users to learn complex drag-and-drop report builders or memorize data hierarchies, modern self-service BI is split into distinct styles tailored to specific user habits.

1. Best for Conversational & Search-Driven Analysis: ThoughtSpot

• The Vibe: ChatGPT or Google Search for your enterprise data.
• How it works: Non-technical users type questions in plain English (e.g., "Show me sales by region for Q3" or "Which product categories had the highest churn last month?" ), and the AI instantly generates the right visualization.
• Why it fits non-tech users: There are no pre-built dashboards to dig through or filters to break. It proactively uncovers trends, anomalies, and answers follow-up questions on the fly.
• Watch-out: It requires clean, well-modeled underlying data. If your warehouse is messy, the search results will drift or confuse users.
• Learn more: Explore capabilities directly on the ThoughtSpot platform overview.

2. Best for Spreadsheet-Fluent Teams (Finance, Ops, Sales): Sigma Computing

• The Vibe: A live, collaborative cloud spreadsheet powered by your data warehouse.
• How it works: It mimics the familiar grid layout, formulas, and pivot tables of Excel or Google Sheets, but it connects directly to modern cloud warehouses (like Snowflake or Databricks) at petabyte scale.
• Why it fits non-tech users: Most business professionals already know how to use a spreadsheet. They can slice, dice, and write basic calculated fields without ever needing to learn SQL or wait for an IT ticket.
• Watch-out: It can encourage "shadow reporting" if users start building massive, ungoverned custom sheets instead of sticking to core organizational metrics.
• Learn more: See how it works via Sigma Computing.

3. Best for the Enterprise Ecosystem & Budget: Microsoft Power BI

• The Vibe: The omnipresent corporate standard with deep Office 365 and Microsoft Fabric integration.
• How it works: Users interact with robust, highly polished interactive dashboards, utilizing embedded AI copilots to ask conversational questions or summarize visual elements.
• Why it fits non-tech users: If your company already lives in Teams, Excel, and Azure, the learning curve is gentle. It is also the most cost-effective enterprise option per user.
• Watch-out: While consuming reports is easy, true ad-hoc self-service exploration often bogs down non-technical users if they have to deal with complex data modeling or DAX formulas under the hood.
• Learn more: Review features on the Microsoft Power BI site.

4. Best for Visual Explorers & Presentation: Tableau

• The Vibe: The gold standard for dynamic, high-end visual data storytelling.
• How it works: Relies on its proprietary drag-and-drop VizQL engine to turn rows of data into rich interactive graphics.
• Why it fits non-tech users: Highly visual thinkers love the speed of dropping dimensions onto a canvas to see patterns immediately.
• Watch-out: Deep self-service exploration and custom formula authoring can carry a steeper learning curve, meaning casual business users usually need structured training.
• Learn more: Check out details on Tableau.

Quick Decision Framework

• Choose ThoughtSpot if your users just want to ask a question in plain English and get an immediate answer.
• Choose Sigma if your business teams live inside spreadsheets and want to crunch numbers safely.
• Choose Power BI if you want low enterprise cost and deep integration with your existing Microsoft stack.
• Choose Tableau if your priority is stunning, advanced visual data exploration.

To help narrow this down, tell me:

• What cloud data warehouse or database are you using (e.g., Snowflake, BigQuery, Postgres)?
• What is the primary background of the business users (e.g., finance/operations vs. general sales/marketing)?

If your goal is specifically “let non-technical business teams answer their own questions without creating a governance nightmare,” I’d shortlist ThoughtSpot, Power BI, Sigma, and Looker/Omni rather than treating all BI platforms as equivalent.

My recommendation

Best overall for business-user self-service: ThoughtSpot

It is particularly strong when users want to ask questions in plain English rather than learn a BI tool: “Why did gross margin fall in the Northeast last month?” → answer, visualization, and follow-up exploration. ThoughtSpot is explicitly designed around search/AI-driven analytics for business users.

But the best choice depends heavily on your existing stack:

Recent 2026 comparisons broadly reach the same conclusion: ThoughtSpot is particularly strong for search-driven business self-service, Power BI for Microsoft-centric organizations, Sigma for spreadsheet-oriented teams, and Looker for governed semantic modeling.

The important caveat

Don't buy “self-service BI”; buy a governed self-service data layer.

The biggest failure mode is giving everyone a friendly interface over raw tables. You'll get:

“Revenue is $12.4M in Finance's dashboard but $11.8M in Sales' dashboard.” The platform should let your data team define canonical metrics—revenue, active customer, churn, gross margin, pipeline, etc.—and then let business users explore those definitions freely. The semantic/governance layer is arguably more important than the visualization layer.

What I'd do in your shoes

• Microsoft-heavy organization: start with Power BI. Its semantic models, Microsoft 365 integration, and natural-language capabilities make it a very pragmatic choice. Microsoft is also moving its legacy Q&A experience toward Copilot, with Q&A scheduled for deprecation in December 2026.
• You want the easiest possible “ask the data a question” experience: evaluate ThoughtSpot first.
• Finance/operations users live in Excel: evaluate Sigma.
• You have a modern warehouse and a strong analytics engineering team: put Omni and Looker on the shortlist, especially if metric governance is paramount.
• You need beautiful, sophisticated visual analytics: put Tableau in the evaluation.

My default shortlist for an enterprise buying process would be ThoughtSpot + Power BI + Sigma + Omni, with Looker added if governance/modeling is the overriding priority.

If you tell me your data warehouse (Snowflake/BigQuery/Databricks/etc.), approximate number of business users, and whether you're already a Microsoft/Salesforce/Google shop, I can narrow that to a winner and give you a vendor scorecard.

Recent 2026 comparisons broadly reach the same conclusion: ThoughtSpot is particularly strong for search-driven business self-service, Power BI for Microsoft-centric organizations, Sigma for spreadsheet-oriented teams, and Looker for governed semantic modeling.

The important caveat

Don't buy “self-service BI”; buy a governed self-service data layer.

The biggest failure mode is giving everyone a friendly interface over raw tables. You'll get:

“Revenue is $12.4M in Finance's dashboard but $11.8M in Sales' dashboard.” The platform should let your data team define canonical metrics—revenue, active customer, churn, gross margin, pipeline, etc.—and then let business users explore those definitions freely. The semantic/governance layer is arguably more important than the visualization layer.

What I'd do in your shoes

If your goal is specifically “let business teams answer their own questions without needing an analyst”, my top pick in 2026 is ThoughtSpot—with Power BI and Sigma as the strongest alternatives depending on your environment.

My shortlist

🥇 Best overall: ThoughtSpot

ThoughtSpot is unusually well aligned with your stated objective: a salesperson, finance manager, marketer, or operations leader can type a business question in natural language and explore the answer without knowing SQL, table relationships, or how to construct a dashboard. Its current platform also includes an AI analyst and interactive drill-downs.

For example:

“Why did gross margin fall in the Northeast last quarter?”

A good self-service platform should let the user go from that question → answer → “break it down by product” → “compare against last year” without filing a ticket with BI.

That's where I'd give ThoughtSpot the edge.

🥈 Power BI if you're a Microsoft shop

If you're already heavily invested in Microsoft 365, Azure, Excel, and Fabric, I'd seriously consider Power BI instead. Microsoft has put substantial effort into Copilot and natural-language report creation, while Power BI gives you a very broad enterprise BI ecosystem.

The trade-off is that Power BI can become an analyst/developer platform first and a business-user platform second if your semantic models, permissions, and reports aren't carefully designed.

🥉 Sigma if your users think in spreadsheets

Sigma is particularly compelling for finance, operations, RevOps, and strategy teams because it deliberately resembles a spreadsheet while operating directly against cloud-warehouse data. Users can filter, pivot, drill and ask questions without coding.

I'd put Sigma ahead of ThoughtSpot if your users' mental model is “give me the data and let me work with it like Excel.”

What I'd choose

• Maximum business-user autonomy: ThoughtSpot
• Microsoft-centric enterprise: Power BI
• Spreadsheet-oriented business teams + Snowflake/Databricks: Sigma
• Best-in-class visualization/storytelling: Tableau — its current Pulse/Agent experience also supports natural-language exploration.
• Google Cloud / highly governed semantic layer: Looker — its 2026 Conversational Analytics lets users ask natural-language questions grounded in the Looker semantic model.
• Highly exploratory enterprise analytics: Qlik — strong combination of drag-and-drop, NLP, augmented analytics and governance.

One important caveat: don't select based primarily on the AI demo. The biggest determinant of successful self-service BI is whether you can establish trusted business definitions, permissions, and a clean semantic layer underneath the experience. Otherwise you simply replace “ask the BI team” with “ask the AI and hope.”

If I were evaluating vendors for your organization, I'd run a bake-off using 10 real questions from Sales, Finance, Marketing, and Operations, and score each platform on time-to-answer, accuracy, follow-up exploration, governance, and how often users still need an analyst. That will tell you much more than a generic feature comparison.

Empowering business teams with self-service BI comes down to balancing ease of use for non-technical users with governance so data stays reliable.

Here are the top self-service BI and analytics platforms tailored for business users, ranked by their strengths:

• Microsoft Power BI stands out as the best overall choice for most organizations, especially those already embedded in the Microsoft 365 ecosystem. It features an intuitive, Excel-like interface, robust natural language querying (allowing users to type questions in plain English), and deeply integrated AI insights.
• Tableau is the gold standard for deep, interactive data visualization and exploration. While its advanced authoring can have a steeper learning curve, its "Ask Data" natural language feature and curated data-source layers make it powerful for business users who want to visually slice and dice data without writing code.
• Looker (by Google Cloud) excels at maintaining a single source of truth through its modeling layer (LookML). Once data models are set up by technical teams, business users can easily explore, drill down, and build reports using simple, pre-defined dimensions and metrics without breaking underlying logic.
• Domo is built specifically for business executives and non-technical teams who need fast, cloud-native integration across hundreds of data sources. It offers consumer-grade dashboards, automated alerts, and low friction for everyday users to track KPIs without IT bottlenecks.
• ThoughtSpot is the premier choice for AI-driven, search-based analytics. It mimics a search engine experience—users type questions like "Show me sales by region last quarter"—making it arguably the most approachable tool for completely non-technical staff.

To help narrow down the best fit, tell me:

• What data stack/warehouses (e.g., Snowflake, BigQuery, Excel, SQL Server) are you currently using?
• Is your organization already heavily invested in a specific ecosystem like Microsoft 365 or Google Workspace?
• What is the technical skill level of your typical end-user?

The best self-service BI and analytics platform for non-technical users depends heavily on your team's workflow and data culture, but ThoughtSpot and Dot lead the market for search-driven and conversational analytics, while Sigma excels for spreadsheet-fluent teams and Microsoft Power BI dominates enterprise Microsoft environments. Choosing the right tool requires matching your users' habits—whether they prefer typing natural language questions, working in familiar spreadsheet grids, or clicking through pre-built visual dashboards.

Top Platforms by Use Case

• ThoughtSpot – Best for search-first, AI-native discovery . It lets users type plain-English questions like a search engine to instantly generate charts and data insights without navigating complex menus.
• Dot – Best for conversational chat workflows embedded directly inside tools like Slack, Teams, or email, eliminating traditional dashboards entirely in favor of direct text answers.
• Sigma – Best for spreadsheet-centric teams (finance, ops). It provides a live, collaborative interface that mimics a web-based spreadsheet while querying modern cloud data warehouses directly.
• Microsoft Power BI – Best for Microsoft-heavy ecosystems . It offers an accessible path of least resistance if your organization already relies heavily on Office 365, Excel, and Azure.
• Metabase – Best for fast, low-cost, or open-source deployments . It features an intuitive, minimalist click-to-explore interface that doesn't overwhelm novice users.
• Tableau – Best for deep visual exploration and rich custom graphing, though it carries a steeper learning curve than pure search tools.

To help narrow down the ideal platform, could you tell me:

• What data warehouse or database do you use (e.g., Snowflake, BigQuery, Postgres)?
• Are your business users comfortable with spreadsheets , or do they prefer chat/search bars?
• What is your approximate user count and budget tier?

If the goal is “business teams answer their own questions without constantly asking Data/IT”, I’d shortlist Power BI, Sigma, Tableau, ThoughtSpot, and Omni—but the best choice depends heavily on your data stack and how much governance you need.

My recommendation

For most enterprises: Microsoft Power BI is the safest default. It has broad self-service capabilities, a mature ecosystem, strong Excel familiarity, and deep Microsoft/Fabric integration. Gartner’s 2025 assessment includes Microsoft among the major ABI platforms, and Microsoft says Power BI has 30M monthly active users.

But if “non-technical self-service” is the primary objective rather than broad enterprise BI, I'd seriously evaluate Sigma and Omni alongside Power BI. Recent 2026 comparisons distinguish them by their spreadsheet/workbook-style exploration and governed self-service approaches.

The key insight

Don't choose based primarily on “how easy is it to make a dashboard?”

The real question is:

Can a business user ask a novel question and get a trustworthy answer without involving an analyst?

That requires three things:

1. A governed semantic layer — “revenue,” “customer,” “churn,” etc. have one agreed definition.
2. Flexible exploration — users can slice, filter, pivot, calculate and combine data without SQL.
3. Natural-language/AI access — increasingly useful for users who don't know how to construct an analysis.

Gartner's 2025 research explicitly emphasizes metrics, natural-language querying, data preparation, governance, and data storytelling as important capabilities—not merely dashboarding.

What I'd do

If I were running the evaluation, I'd run a 2–4 week proof of concept with 20–30 real users from Finance, Sales, Marketing, and Operations. Give every vendor the same 10–15 real business questions, including questions that aren't already represented by an existing dashboard.

Score them on:

• Can a non-technical user answer it unaided?
• Time to answer
• Accuracy vs. the company's trusted numbers
• Ability to drill from summary → underlying data
• Ability to create a new analysis without IT
• AI/natural-language quality
• Governance and permissions
• Ease of maintaining metrics
• Adoption after initial training
• Total cost at your expected user count

My likely shortlist:
Power BI if you're Microsoft-centric; Sigma if your business users live in spreadsheets; Omni if you're warehouse-first and want governed self-service; ThoughtSpot if conversational/AI analytics is the centerpiece.

If you tell me your data stack (Snowflake/Databricks/BigQuery/etc.), approximate employee count, Microsoft/Google environment, and whether Finance/Operations or Sales/Marketing are the main users, I can narrow this to a specific winner and a vendor-by-vendor evaluation matrix.