# Supaboard

> Supaboard is the one AI agent that does the whole analyst job on your own database: answers with the SQL shown, dashboards, reports and alerts. Viewers are free.

Supaboard is an AI agent for data analysis and business intelligence that works on your own database.

For operators at companies with 50 to 500 staff whose business runs on a database but who cannot staff a data team, Supaboard is the one AI agent that does the whole analyst job: it answers questions on your live data and shows its working, builds the dashboards, reports and decks, runs the weekly review and the alerts on its own, builds internal tools and sheets, learns your definitions from every correction, and proves its accuracy on questions you already know the answers to. Unlike BI platforms that sell each job as an add-on, chat tools that stop at the answer, and warehouse AI that only serves its own customers, Supaboard does all of it from one agent, on your own database, with free viewers for everyone who reads the result.

Every chart and number comes with the query that produced it, and your agent reads your business definitions with every question. Database and warehouse queries are read-only. Changes to connected apps require your approval.

- Connectors: 12 databases and warehouses, queried read-only when a question is asked, and any tool with an MCP server, read live by agents (22 are ready to add), across 5 categories (Databases & warehouses, CRM & payments, Product & engineering, Docs & files, Communication & calendars). Nothing is synced. Spreadsheets and documents can also be attached to a conversation.
- Plans: Free ($0, no credit card), Starter ($19/editor/month, or $16/editor/month billed annually — $190/editor/year), Individual ($99/editor/month, or $83/editor/month billed annually — $990/editor/year), Business ($249/editor/month, or $208/editor/month billed annually — $2,490/editor/year), Enterprise (custom). Prices are per editor, and the Free plan needs no credit card.
- Product docs live at https://docs.supaboard.ai; the app itself is at https://web.supaboard.ai.
- Machine-readable indexes: https://supaboard.ai/sitemap.xml and https://supaboard.ai/blog/rss.xml.
- Every page below is also served as markdown: append `.md` to its path (https://supaboard.ai/pricing.md), or request it with `Accept: text/markdown`.
- Published by Fyipen Private Limited, #210, 16th Main, Yellukunte, Indira Canteen Road, Bengaluru, Karnataka, India. Contact founders@supaboard.cloud.

## Core pages

- [Supaboard](https://supaboard.ai/): Supaboard is the one AI agent that does the whole analyst job on your own database: answers with the SQL shown, dashboards, reports and alerts. Viewers are free.
- [Pricing](https://supaboard.ai/pricing): Per-editor plans, AI modes, quotas and storage. Free ($0, no credit card), Starter ($19/editor/month, or $16/editor/month billed annually — $190/editor/year), Individual ($99/editor/month, or $83/editor/month billed annually — $990/editor/year), Business ($249/editor/month, or $208/editor/month billed annually — $2,490/editor/year), Enterprise (custom).
- [Blog](https://supaboard.ai/blog): Insights, tips and updates. 52 posts.
- [Comparisons](https://supaboard.ai/compare): Supaboard against other BI platforms, with every competitor figure sourced to its own pages. 24 vendors.
- [Enterprise](https://supaboard.ai/enterprise): Self-hosting in your own VPC, bring-your-own-key inference, SOC 2 Type II, HIPAA BAA on request, forward-deployed engineers.

## Product

- [AI Analyst](https://supaboard.ai/product/ask-analysts): Text-to-SQL on your own database: ask in your own words and get the chart, the numbers and the SQL behind them, in Supaboard, Slack, Claude or ChatGPT.

## Answers & artifacts

- [Answers & artifacts](https://supaboard.ai/product/answers-and-artifacts): Ask on your live data, dig deeper when you need to, turn the analysis into a PDF report, then keep it working as a live dashboard, a datasite or an automation.
- [Dashboards](https://supaboard.ai/product/dashboards): An AI dashboard generator for your own data: describe what you want to track and get a live dashboard, with 20+ chart types and filters that carry across it.
- [Datasites](https://supaboard.ai/product/datasites): Describe the site you need and Supaboard builds it from your live data, in your brand, on a link you can send or embed in your own product. No front-end work and no hosting to arrange.
- [Automations](https://supaboard.ai/product/automations): Automated reporting on your own data: run analysis on a schedule or when an alert fires, then send a PDF, PowerPoint or Excel report by email or webhook.

## Connect your data

- [Connect your data](https://supaboard.ai/product/data-connections): Upload files or connect databases and data warehouses. Ask about each source or combine their results, and see how each one is read, how current it is and what setup needs.
- [Upload files](https://supaboard.ai/product/file-uploads): Add a CSV, Excel file, PDF, Word document or image to a Supaboard conversation. Compare figures, extract key details, or check it against a connected database or warehouse.
- [Databases](https://supaboard.ai/product/databases): Connect PostgreSQL, MySQL, SQL Server, Oracle, MongoDB or Supabase. Your team asks in plain English; Supaboard runs read-only queries when you ask and shows the query behind each result.
- [Data warehouses](https://supaboard.ai/product/data-warehouses): Connect Snowflake, BigQuery, Redshift, Databricks, ClickHouse or MotherDuck so more of your team can explore the tables your data team maintains. Queries run in your warehouse, as the account you connect.

## Up close with your data

- [Up close with your data](https://supaboard.ai/product/up-close): Write SQL or Python in Query Bench and work through the rows in Sheets. Pin results to dashboards, and use sheets as a data source for AI Analyst, automations and datasites.
- [Query Bench](https://supaboard.ai/product/query-builder): An AI SQL and Python editor for your connected sources: schema-aware autocomplete, AI edits you approve, and results you pin to a dashboard.
- [Sheets](https://supaboard.ai/product/sheets): Start from a query result, a workbook or a blank sheet and work together with familiar formulas. Then use your tables in AI Analyst, agents, automations and datasites.

## Answers you can check

- [Agents](https://supaboard.ai/product/agents): A Supaboard agent gives AI Analyst your data and your team’s context: rules, reviewed SQL examples and what it learns from feedback, with evals to test its answers.
- [Knowledge & rules](https://supaboard.ai/product/knowledge-and-rules): Give a Supaboard agent your definitions, reference documents, table notes and repeat tasks in plain language. Rules are read with every question; documents and skills when a question needs them.
- [Examples](https://supaboard.ai/product/agent-examples): Pair a question your team asks with SQL you’ve run and reviewed. A Supaboard agent reads its examples before it answers, and marks answers whose SQL matches one.
- [Memory](https://supaboard.ai/product/agent-memory): A Supaboard agent keeps useful context from conversations and feedback, for everyone using it or just the person who said it. Review, edit or delete any memory.
- [Evals](https://supaboard.ai/product/evals): Evals pair your real questions with the SQL that answers them. Run them against a Supaboard agent, inspect what fails, and compare runs after every change.

## Industries

- [Supaboard by Industry: Healthcare, Logistics, Manufacturing, Software](https://supaboard.ai/industry): What teams in healthcare, transportation and logistics, manufacturing, and software and commerce ask Supaboard, keep on a schedule and connect.
- [Healthcare RCM Analytics: Denials, AR Aging and SLAs](https://supaboard.ai/industry/revenue-cycle-management): Ask claims and billing data about denials by payer, AR by aging bucket, days to bill and client SLAs, then keep watch over them. HIPAA BAA available.
- [Medical and Dental Practice Analytics: No-Shows, Production](https://supaboard.ai/industry/medical-practices): Ask your practice system about no-shows and schedule fill by location, production by provider, collections, recalls and case acceptance. HIPAA BAA available.
- [Home and Senior Care Analytics: Visits, Overtime, Shifts](https://supaboard.ai/industry/senior-care): Ask scheduling, EVV and payroll data about authorised against delivered hours, missed visits, caregiver overtime, open shifts and census. HIPAA BAA available.
- [Pharmacy Analytics: Margin by PBM, Rejects, Refills, Stock](https://supaboard.ai/industry/pharmacies): Ask your pharmacy system's data about scripts per pharmacist, margin by PBM, rejected claims, reversals, dead stock and refills due. HIPAA BAA available.
- [Fuel and Propane Delivery Reporting: Trucks, Tanks, Drivers](https://supaboard.ai/industry/fuel-distribution): Ask your dispatch database about deliveries per truck, tank run-outs and driver hours, then schedule the end-of-day report and the run-out alert.
- [Trucking Analytics: Revenue per Mile, Deadhead, Detention](https://supaboard.ai/industry/trucking): Ask your TMS about revenue per mile by lane, empty miles, on-time delivery by customer and unbilled detention, then get the lane scorecard every Monday.
- [Last-Mile Delivery Analytics: First Attempts, Cost per Drop](https://supaboard.ai/industry/last-mile-delivery): Ask route and dispatch data about first-attempt delivery, missed windows, failed stops by reason and cost per drop, then get yesterday's late routes by 06:00.
- [3PL Warehouse Analytics: On-Time, Accuracy, Dock-to-Stock](https://supaboard.ai/industry/warehousing): Ask your WMS about orders shipped on time per client, pick accuracy, dock-to-stock hours and storage billed, then send every client a weekly SLA report.
- [Precision Manufacturing Analytics on ERP Data, in ₹ Lakhs](https://supaboard.ai/industry/precision-manufacturing): Ask your ERP about rejection by operation, on-time delivery, department costs, debtors and MSME dues in ₹ lakhs, and send the monthly MIS on a schedule.
- [Food Manufacturing Analytics: Yield, Giveaway, Batch Cost](https://supaboard.ai/industry/food-manufacturing): Ask production and ERP data about yield against recipe, giveaway by filler, batch cost, QA holds and short-dated stock, and get yesterday by line each morning.
- [Wholesale Distribution Analytics: Margin, Fill Rate, Ageing](https://supaboard.ai/industry/wholesale-distribution): Ask your ERP about margin by customer after schemes, fill rate, stock ageing, debtors by salesperson and price variance, and get the Monday review on its own.
- [Construction Job Cost Analytics: WIP and Change Orders](https://supaboard.ai/industry/construction): Ask your job-cost ledger about cost to complete, over and under billing, pending change orders, retainage and labour by cost code, and send the WIP monthly.
- [SaaS Analytics: MRR Movements, NRR, Churn and Activation](https://supaboard.ai/industry/saas): Ask billing, product and CRM data about MRR movements, NRR by cohort, trial-to-paid, activation and accounts at risk, then get the MRR bridge every Monday.
- [Subscription Box Analytics: Subscribers, Churn and Gifting](https://supaboard.ai/industry/subscription-boxes): Ask billing and store data about active subscribers, gift-to-paid conversion, failed payments by decline code, churn by box and skips before cut-off.
- [Ecommerce Analytics: Profit After Ads, Stock, Repeat Buyers](https://supaboard.ai/industry/ecommerce): Ask store, marketplace, retail and ad data about profit after ads, MER, stock cover and repeat buyers, then get profit by channel in your inbox every Monday.
- [Ed-Tech Analytics: Enrolments, Completion and Renewals](https://supaboard.ai/industry/edtech): Ask your learning platform's data about enrolments, course completion, learners gone quiet, assessment pass rates and seats activated for each B2B customer.

## Comparisons

- [Supaboard vs Power BI](https://supaboard.ai/compare/power-bi): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Power BI's own pages, plus why teams choose Supaboard over Power BI.
- [Supaboard vs Metabase](https://supaboard.ai/compare/metabase): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Metabase's own pages, plus why teams choose Supaboard over Metabase.
- [Supaboard vs ThoughtSpot](https://supaboard.ai/compare/thoughtspot): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to ThoughtSpot's own pages, plus why teams choose Supaboard over ThoughtSpot.
- [Supaboard vs Looker](https://supaboard.ai/compare/looker): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Looker's own pages, plus why teams choose Supaboard over Looker.
- [Supaboard vs Qlik](https://supaboard.ai/compare/qlik): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Qlik's own pages, plus why teams choose Supaboard over Qlik.
- [Supaboard vs Domo](https://supaboard.ai/compare/domo): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Domo's own pages, plus why teams choose Supaboard over Domo.
- [Supaboard vs Sigma](https://supaboard.ai/compare/sigma): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Sigma's own pages, plus why teams choose Supaboard over Sigma.
- [Supaboard vs Omni](https://supaboard.ai/compare/omni): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Omni's own pages, plus why teams choose Supaboard over Omni.
- [Supaboard vs Zenlytic](https://supaboard.ai/compare/zenlytic): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Zenlytic's own pages, plus why teams choose Supaboard over Zenlytic.
- [Supaboard vs WisdomAI](https://supaboard.ai/compare/wisdom-ai): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to WisdomAI's own pages, plus why teams choose Supaboard over WisdomAI.
- [Supaboard vs TextQL](https://supaboard.ai/compare/textql): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to TextQL's own pages, plus why teams choose Supaboard over TextQL.
- [Supaboard vs Sundial](https://supaboard.ai/compare/sundial): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Sundial's own pages, plus why teams choose Supaboard over Sundial.
- [Supaboard vs Wren AI](https://supaboard.ai/compare/wren-ai): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Wren AI's own pages, plus why teams choose Supaboard over Wren AI.
- [Supaboard vs Basedash](https://supaboard.ai/compare/basedash): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Basedash's own pages, plus why teams choose Supaboard over Basedash.
- [Supaboard vs Hex](https://supaboard.ai/compare/hex): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Hex's own pages, plus why teams choose Supaboard over Hex.
- [Supaboard vs Lightdash](https://supaboard.ai/compare/lightdash): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Lightdash's own pages, plus why teams choose Supaboard over Lightdash.
- [Supaboard vs Julius AI](https://supaboard.ai/compare/julius-ai): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Julius AI's own pages, plus why teams choose Supaboard over Julius AI.
- [Supaboard vs Bruin](https://supaboard.ai/compare/bruin): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Bruin's own pages, plus why teams choose Supaboard over Bruin.
- [Supaboard vs Snowflake Cortex Analyst](https://supaboard.ai/compare/snowflake-cortex): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Snowflake Cortex Analyst's own pages, plus why teams choose Supaboard over Snowflake Cortex Analyst.
- [Supaboard vs Databricks Genie](https://supaboard.ai/compare/databricks-genie): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Databricks Genie's own pages, plus why teams choose Supaboard over Databricks Genie.
- [Supaboard vs Amazon QuickSight](https://supaboard.ai/compare/amazon-quicksight): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Amazon QuickSight's own pages, plus why teams choose Supaboard over Amazon QuickSight.
- [Supaboard vs ChatGPT](https://supaboard.ai/compare/chatgpt): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to ChatGPT's own pages, plus why teams choose Supaboard over ChatGPT.
- [Supaboard vs Claude](https://supaboard.ai/compare/claude): Price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy compared, each figure sourced to Claude's own pages, plus why teams choose Supaboard over Claude.

## Blog

- [AI data analytics benchmark: 9 agents, one messy database](https://supaboard.ai/blog/ai-data-analytics-benchmark): data — Compare 9 AI data agents on a messy SaaS database. See reported scores, CRM-matching failures, response times, and the limits of the Data Analytics Index.
- [Financial Dashboard Examples: Why Cash Gets Tight as Sales Grow](https://supaboard.ai/blog/financial-dashboard-examples): data — Explore three financial dashboard examples with a receivables aging chart, invoice actions and a KPI worksheet that connects each metric to a review question.
- [Cohort retention: a good first week can hide a bad trend](https://supaboard.ai/blog/cohort-retention-analysis): product — A strong first week can hide declining retention. Learn what cohort curves reveal about recurring value, product improvements, and sustainable SaaS growth.
- [Why we changed how Supaboard’s AI works](https://supaboard.ai/blog/why-we-changed-how-supaboard-ai-works): company — Why we rebuilt Supaboard’s AI around one conversation: a founder’s account of carrying context from an investigation into dashboards and recurring reports.
- [Retail Business Intelligence: KPIs, Dashboards & Tools](https://supaboard.ai/blog/retail-business-intelligence): data — Retail BI turns sales, inventory, customer and margin data into decisions. The KPIs that matter, the dashboard each team needs, and the pitfalls to avoid.
- [Apache Superset alternatives: BI tools compared](https://supaboard.ai/blog/apache-superset-alternatives): product — Apache Superset is free to license and costs real engineering time to run. How the alternatives compare on governance, support and total cost of ownership.
- [Sisense Alternatives: 7 BI Tools Compared in 2026](https://supaboard.ai/blog/sisense-alternatives): product — Comparing Sisense alternatives in 2026? See how Supaboard, ThoughtSpot, Power BI, Looker, Metabase, Domo, and Qlik Sense stack up on setup, AI, and price.
- [One AI Agent for the Whole Analyst Job: Tools Compared (2026)](https://supaboard.ai/blog/ai-data-analyst): engineering — An AI data analyst answers questions against governed definitions instead of raw schema. How it works, what it automates, and what it cannot.
- [From 4 Hours to 2 Minutes: An RCM Analytics Rebuild](https://supaboard.ai/blog/from-4-hours-to-2-minutes-rcm-analytics): company — A revenue cycle management company cut per-client analysis from four hours to two minutes, with every piece of patient data masked before it ever moved.
- [What Is a Semantic Layer? The 2026 Field Guide](https://supaboard.ai/blog/what-is-a-semantic-layer): engineering — A founder's field guide to the semantic layer in 2026: what it is, why AI agents fail without one, and how dbt, Cube, AtScale, Looker, and Malloy compare.
- [How to Evaluate AI BI Tools: 12 Questions for Demos](https://supaboard.ai/blog/how-to-evaluate-ai-bi-tools): product — Most AI BI demos are rehearsed against prepared data. Twelve questions that separate a working product from a well-practised sales presentation.
- [Is AI BI Just Text-to-SQL? The Honest Difference (With Examples)](https://supaboard.ai/blog/is-ai-bi-just-text-to-sql): engineering — Text-to-SQL turns a question into a query. AI-native BI understands the business. Here's the real difference, with a worked NRR example and a 5-min test.
- [10 Best Data Visualization Tools in 2026 (Compared)](https://supaboard.ai/blog/data-visualization-tools): product — Compare the 10 best data visualization tools of 2026, from Power BI and Tableau to Looker Studio, on features, pricing at scale and AI, and pick the right one.
- [Analytics Without a Data Team: A Practical Guide](https://supaboard.ai/blog/analytics-without-a-data-team): company — How teams with no analysts build a single source of truth, agree on shared metric definitions, and answer their own data questions without joining a queue.
- [Positive vs Negative Correlation: Meaning + Examples](https://supaboard.ai/blog/positive-vs-negative-correlation): data — Positive correlation: variables rise together. Negative: one rises as the other falls. Real examples, plus a table for reading the coefficient from -1 to +1.
- [Spend Analytics: Tools, Use Cases and Best Practices](https://supaboard.ai/blog/spend-analytics): data — Spend analytics turns scattered procurement data into savings you can act on, and the use cases that reliably pay back before all the others do.
- [AI Contextual Governance: A 4-Layer Framework](https://supaboard.ai/blog/ai-analytics-governance): engineering — AI contextual governance adapts data access rules to who is asking and why. See the 4-layer framework, a real-world example, and why static AI rules fail.
- [Top ThoughtSpot Alternative in 2026: Best Tools Compared](https://supaboard.ai/blog/thoughtspot-alternatives): product — ThoughtSpot pioneered search-style analytics at enterprise prices. How alternatives compare on setup cost, modelling and time to first answer.
- [AI Predictive Analytics in Healthcare: A Practical Guide](https://supaboard.ai/blog/healthcare-analytics): data — Healthcare analytics is constrained first by what data may legally move. How masking, prediction and explainability fit together in practice.
- [Manufacturing Analytics: Why It Matters More Than Ever in 2026](https://supaboard.ai/blog/manufacturing-analytics): data — Manufacturing analytics joins machine telemetry to commercial outcomes. Where predictive maintenance pays back, and where it quietly does not at all.
- [Database Optimization: 5 Layers to Faster Queries](https://supaboard.ai/blog/database-optimization): engineering — What database optimization is and how to do it without buying more hardware: design, indexing, schema, infrastructure and concurrency, explained layer by layer.
- [One Analyst Agent vs Traditional BI: What Changes](https://supaboard.ai/blog/agentic-analytics): product — Traditional BI tells you what happened. Agentic analytics runs the investigation. How the two differ, and three demo tests that separate them.
- [Power BI vs Tableau (2026): Pricing, Pros & Cons](https://supaboard.ai/blog/power-bi-vs-tableau): product — Power BI vs Tableau compared on pricing, ease of use, visualization, data modeling and real user complaints, so you can pick the right BI tool for your team.
- [Metabase Alternatives Compared for 2026](https://supaboard.ai/blog/metabase-alternatives): product — Metabase is easy to start with and awkward to white label. How the alternatives compare on embedding, multi-tenancy, support and on pricing shape.
- [Natural Language Query Analytics: A 2026 Guide](https://supaboard.ai/blog/natural-language-query-analytics): data — Ask a data question in plain English and get a real answer back. How NLQ works, where it earns its keep, and the prerequisite that vendors gloss over.
- [Histogram vs Bar Graph: Key Differences + Examples](https://supaboard.ai/blog/bar-graph-vs-histogram): data — A bar graph compares categories; a histogram shows how numbers are distributed. See side-by-side charts, a comparison table, and when to use each.
- [AI Business Intelligence Tools: The AI-Native Shortlist](https://supaboard.ai/blog/ai-native-business-intelligence-tools): product — Which AI BI tools are truly AI-native, not a chatbot bolted onto a dashboard: ThoughtSpot, Hex, Omni, Supaboard and more, plus 3 demo questions to ask.
- [Data Engineering in 2027: What Skills Will Still Matter?](https://supaboard.ai/blog/data-engineering): engineering — What data engineers actually do now that pipelines became a commodity, which parts of the job automate away, and which judgement calls never will.
- [Data Connectivity: What It Is and How It Works](https://supaboard.ai/blog/data-connectivity): engineering — Data connectivity links your databases, apps and BI tools so data flows between them. How it works step by step, plus the hidden costs of poor connectivity.
- [8 Best AI BI Tools in 2026 (Compared, With Pricing)](https://supaboard.ai/blog/best-ai-bi-tools): product — 8 AI BI tools, including Power BI, Tableau, ThoughtSpot and Looker, compared on AI depth, setup effort and real pricing, with the best pick for each use case.
- [Self-Service BI vs Traditional BI: Key Differences](https://supaboard.ai/blog/self-service-bi): data — Self-service BI lets business users answer data questions without an analyst. How it differs from traditional BI, with examples and governance trade-offs.
- [Enterprise Business Intelligence: Use Cases and Tools](https://supaboard.ai/blog/enterprise-business-intelligence): data — Enterprise BI is defined by governance as much as by analysis. The use cases, the tools, and why definitions matter far more than the dashboards do.
- [What Is a Real-Time Analytics Platform? Complete Guide (2026)](https://supaboard.ai/blog/real-time-analytics): data — Real-time analytics narrows the gap between what happens and what you know. How it differs from business activity monitoring, and when to buy.
- [Ecommerce Analytics: Dashboards, KPIs & Examples](https://supaboard.ai/blog/ecommerce-analytics): data — Which ecommerce metrics to track, what a good ecommerce dashboard contains, real examples, and how to use analytics to find and fix cart abandonment.
- [What Is Business Intelligence? Complete Guide for Businesses](https://supaboard.ai/blog/business-intelligence): data — Business intelligence turns operational data into decisions people actually make. What it covers, how it evolved, and why most BI failures are definitional.
- [Database vs Data Warehouse vs Data Lake: Differences](https://supaboard.ai/blog/database-vs-data-warehouse-vs-data-lake): engineering — A database runs transactions, a data warehouse powers analysis, a data lake stores raw data. Compare all three side by side, with examples and when to use each.
- [How Generative AI Is Transforming Business Intelligence](https://supaboard.ai/blog/generative-business-intelligence): data — Discover how generative business intelligence uses AI to deliver real-time insights, natural language analytics, and faster decision-making.
- [BI Dashboard: Types, Examples & Key Features](https://supaboard.ai/blog/bi-dashboards): data — A BI dashboard shows the metrics behind a decision at a glance. Operational, analytical and strategic examples, must-have features, and mistakes to avoid.
- [What Is dbt? How It Works and When to Use It](https://supaboard.ai/blog/dbt): engineering — dbt (data build tool) turns SQL into tested, version-controlled data models. What it is, why it is not ETL, where MetricFlow fits, and when it is overkill.
- [What is a KPI? Real Examples for SaaS & Business Teams](https://supaboard.ai/blog/what-is-a-kpi): data — A KPI is a measure tied to a decision somebody makes. How to choose them, define them so teams agree, and tell them from ordinary statistics.
- [What Is Predictive Analytics? Simple Guide](https://supaboard.ai/blog/what-is-predictive-analytics): data — Predictive analytics estimates outcomes from historical patterns. How it works, what bounds its accuracy, and when a forecast is worth trusting.
- [Best Looker Alternatives for Modern Analytics in 2026](https://supaboard.ai/blog/looker-alternatives): product — Find the best Looker alternatives for modern analytics. Compare Looker-like BI tools for enterprises, from AI-powered platforms to open-source options.
- [4 Types of Analytics: Descriptive to Prescriptive](https://supaboard.ai/blog/types-of-analytics): data — Descriptive, diagnostic, predictive and prescriptive analytics explained with examples, a comparison table, and the order to build them in so forecasts hold up.
- [What Is an Ad Hoc Query? Meaning + SQL Examples](https://supaboard.ai/blog/what-is-an-ad-hoc-query): data — An ad hoc query is a one-off question asked of your data, outside any scheduled report. Its meaning, SQL examples, and how it differs from ad hoc reporting.
- [Logistics Analytics: Turning Supply Chain Data Into Action](https://supaboard.ai/blog/logistics-analytics): data — Logistics analytics is about exceptions, not averages. Which signals matter, why aggregate on-time rates mislead, and how to join the systems.
- [15 SaaS Metrics That Actually Drive Growth (With Examples)](https://supaboard.ai/blog/saas-business-intelligence): data — SaaS metrics only ever mean something together. How to join product, billing and CRM data, and where cohort logic most quietly goes wrong on you.
- [Tableau Alternatives: Top BI Tools Compared in 2026](https://supaboard.ai/blog/tableau-alternatives): product — Tableau is strong for visual exploration and priced accordingly. How the alternatives compare, and when the whole category is wrong for you.
- [What Is Data Modeling? Types, Tools and Examples](https://supaboard.ai/blog/what-is-data-modeling): engineering — Data modeling defines the entities and relationships a business runs on. The types, the tools, and how the model decides what you are able to ask.
- [Data Science vs Data Analytics: What You Need To Know](https://supaboard.ai/blog/data-science-vs-data-analytics): data — Data analytics explains what happened; data science predicts what will. Where the roles overlap, where they do not, and which one you probably need.
- [Will AI Replace Data Analysts? What the Job Becomes](https://supaboard.ai/blog/will-ai-replace-data-analysts): engineering — Short answer: no, but the job is changing. What AI already automates in data analysis, what it still cannot do, and the skills analysts need to stay relevant.
- [Embedded Analytics: How It Works and What It Costs](https://supaboard.ai/blog/embedded-analytics): product — Embedded analytics puts insight inside your own product. How it works, what white labelling adds, and why per-seat pricing breaks down badly at scale.
- [What Is an AI Dashboard? How It Works vs Static BI](https://supaboard.ai/blog/ai-dashboard-explained): product — An AI dashboard builds charts from a plain-English question instead of manual setup. How it works, where it beats static dashboards, and where it falls short.

## Optional

- [Documentation](https://docs.supaboard.ai): Setup, build and scale guides.
- [Privacy Policy](https://supaboard.ai/privacy-policy): How Supaboard handles personal data.
- [Terms & Conditions](https://supaboard.ai/terms-and-conditions): Terms of service.