DataChat App

Conversational analytics; query data in plain English.

Reviewed by 7wData

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Publisher review

DataChat is a cloud-hosted analytics platform that lets business users query data in plain English instead of writing SQL. Founded in 2017 by researchers at the University of Wisconsin–Madison, it translates conversational queries into SQL and Python through an agentic LLM framework, then executes them against your data warehouse—Snowflake, BigQuery, Databricks, or Postgres. All computation happens within your database; data is never sent to the LLM.

The platform pairs the query engine with a spreadsheet-like interface where users can ask follow-up questions, refine analyses, and build reproducible workflows (documented in DataChat's proprietary Guided English Language format). The platform generates visualizations automatically and supports predictive analytics and data preparation tasks. It's positioned for analysts and business stakeholders who want faster turnaround on analytics without SQL expertise.

DataChat launched as a Snowflake Native App in February 2025 and announced an incoming Slack API for real-time queries in Slack. The company secured Gartner's attention as one of only 15 startups in the 2024 Emerging Tech: Techscape for Startups in Generative AI. Trade-offs matter: users report slow interface loading, and the tool struggles with complex workflows or advanced statistical analysis.

Like all text-to-SQL systems, it hallucinates—inventing columns or misunderstanding schema—especially on ambiguous natural-language questions. The platform's no-code promise works well for ad-hoc exploration but can feel limiting once you hit analytical edge cases. Pricing is custom-quoted; AWS Marketplace lists a $12,000/year entry tier (Starter Pack, non-refundable 12-month contract). Free trial available on the vendor site.

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How it works

  1. Natural language queries

    Type or speak questions in English; the system translates them to SQL and executes against your warehouse.

  2. Automatic visualization

    Results return as charts, tables, or summaries without manual dashboard configuration.

  3. Reproducible workflows (GEL)

    Analyses are logged in Guided English Language, a structured format that shows exactly what query ran and why, enabling auditing and reuse.

  4. In-database compute

    All processing stays inside your Snowflake, BigQuery, or Databricks account; raw data is never sent to external LLMs.

  5. Data transformation and preparation

    Clean, filter, and reshape data before analysis using natural language commands.

  6. Predictive analytics and ML

    Build machine learning models for forecasting and classification without coding.

  7. Slack integration (beta)

    Query your data and receive real-time answers directly in Slack without leaving the chat interface.

Strengths and trade-offs

Strengths

  • Intuitive for non-technical users; fast exploratory analysis without SQL skills.
  • Secure by design: compute runs inside your warehouse, no data export to third parties.
  • Reproducible workflows and audit trail; each analysis is documented in GEL for compliance and knowledge reuse.

Trade-offs

  • Slow UI loading reported in reviews; performance inconsistent on large datasets.
  • Limited customization for complex statistical analysis and advanced workflows beyond ad-hoc Q&A.
  • Text-to-SQL hallucinations: system can mismap natural language to schema, invent columns, or misunderstand ambiguous queries—a known industry-wide risk with LLM-based SQL generation.

Pricing context

DataChat operates on a commercial subscription model with custom enterprise pricing. AWS Marketplace entry point is $12,000/year (Starter Pack, 12-month contract, non-refundable). Free trial offered on the company website. Pricing appears to scale with usage and data warehouse size; contact sales for exact terms based on your data volume and integration complexity.

Getting started with DataChat App

  1. Sign up for trial or enterprise

    Create an account on DataChat's website to access a free trial, or contact sales for an enterprise plan. AWS Marketplace offers a Starter Pack tier starting at $12,000 per year.

  2. Connect your data warehouse

    Authenticate DataChat to your Snowflake, BigQuery, Databricks, or PostgreSQL warehouse by providing connection credentials in the web interface. DataChat discovers available tables and schemas automatically. Your raw data never leaves the database.

  3. Review tables and column structure

    Examine the available tables, columns, and data types in your warehouse through DataChat's interface. Familiarity with your data structure helps you write more precise natural language questions and avoid hallucination errors.

  4. Ask your first query

    Type a plain-English question about your data, such as 'What were sales by region in Q1?' DataChat translates the query to SQL, executes it in your warehouse, and displays results in charts and tables without manual dashboard configuration.

  5. Save and share your analysis

    Save your completed analysis so your team can audit and reuse exactly what you queried and how. Share results directly in Slack (beta) so your team can provide feedback in context.

Frequently Asked Questions

What is DataChat?

DataChat is a cloud-hosted analytics platform founded in 2017 that translates plain English questions into SQL and executes them against your data warehouse—Snowflake, BigQuery, Databricks, or Postgres. The system uses an agentic LLM framework to handle conversational queries and exploratory analysis without requiring SQL expertise.

How does DataChat keep data secure?

All computation happens inside your data warehouse—Snowflake, BigQuery, or Databricks. Raw data is never sent to external LLMs or third parties. Your data remains fully isolated, meeting compliance requirements while the platform translates queries and executes analysis locally within your secure infrastructure.

What does DataChat cost?

DataChat offers custom enterprise pricing based on your data volume and warehouse size. The AWS Marketplace entry point is $12,000 per year for the Starter Pack under a non-refundable 12-month contract. A free trial is available on the company website to evaluate the platform.

Can you use DataChat without SQL knowledge?

DataChat excels at ad-hoc exploration and is intuitive for non-technical business users and analysts. However, it struggles with complex workflows and advanced statistical analysis beyond exploratory queries. The platform works best for rapid turnaround on straightforward questions rather than enterprise-scale, multi-step analytical pipelines.

What are DataChat's main limitations?

DataChat users report slow interface loading and inconsistent performance on large datasets. The platform struggles with text-to-SQL hallucinations—inventing columns or misinterpreting schema, especially on ambiguous queries. These are known industry-wide risks with LLM-based SQL generation, not unique to DataChat.

Does DataChat integrate with Slack?

DataChat announced an incoming Slack API enabling real-time data queries directly within Slack conversations. This integration is currently in beta and will allow users to query their data warehouse and receive answers without leaving the chat interface, streamlining analytics workflows.

Alternatives in this category

Integrations

Snowflake BigQuery Databricks Postgres

How DataChat App compares

Direct head-to-head against 3 competitors. Picked by 7wData.

This tool

DataChat App

Pricing
DataChat operates on a commercial subscription model with custom enterprise pricing. AWS Marketplace entry point is $12,000/year (Starter Pack, 12-month contract, non-refundable). Free trial offered on the company website. Pricing appears to scale with usage and data warehouse size; contact sales for exact terms based on your data volume and integration complexity.
Target
DataChat is a cloud-hosted analytics platform that lets business users query data in plain English instead of writing SQL.
Deployment
cloud
Strength
Intuitive for non-technical users; fast exploratory analysis without SQL skills.
Watch for
Slow UI loading reported in reviews; performance inconsistent on large datasets.

ThoughtSpot

Pricing
Essentials $25/user/month, Pro $50/user/month (25 Spotter AI queries/month cap, overage ~$0.10/query), Enterprise custom from ~$400,000/year.
Target
Large enterprises in retail, financial services, and technology needing non-technical users to query complex data warehouses.
Deployment
SaaS cloud (AWS, GCP, Azure) or on-premises. Available on AWS Marketplace.
Strength
Natural language search across star and snowflake schemas natively, without flattening data or requiring SQL from business users.
Watch for
Pro plan's 25-query/month Spotter cap triggers per-query overage fees; background system queries bill silently under embedded consumption pricing.

Metabase

Pricing
Open source free (self-hosted), Starter $100/month plus $6/user, Pro $575/month plus $12/user, Enterprise from ~$20,000/year.
Target
Startups and SaaS product teams wanting self-service dashboards without SQL, especially those embedding analytics into their own products.
Deployment
Open source self-hosted (Docker, Kubernetes, any Java server), managed SaaS cloud, or paid self-hosted Pro/Enterprise.
Strength
White-label interactive embedding lets SaaS teams ship full dashboards inside their product via iframe at no other open-source tool's price point.
Watch for
Iframe-only embedding cannot be restyled to match your design system; per-seat pricing applies to embedded end-users, scaling costs sharply.

Power BI

Pricing
Pro $14/user/month, Premium Per User $24/user/month, Fabric F2 capacity $262.80/month, F64 (Copilot minimum) ~$5,000/month.
Target
Enterprise BI and analytics teams in Microsoft-first organizations, deployed in 97% of Fortune 500 companies.
Deployment
SaaS via Microsoft Fabric, on-premises via Power BI Report Server (bundled with SQL Server), or hybrid combining both.
Strength
Native first-class embedding inside Microsoft Teams and live PivotTable connections to Power BI datasets directly within Excel, no separate auth required.
Watch for
Copilot requires Fabric F64 capacity (~$5,000/month minimum), not included in Premium Per User ($24/user), a distinction many teams discover after purchase.

User reviews

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Sources

Reporting on this tool draws on these publicly available sources.

  1. aws.amazon.com — Pricing ($12,000/year Starter Pack), deployment model, features, support channels.
  2. www.businesswire.com — Snowflake Native App launch (February 2025), product positioning, integrations.
  3. medium.com — Technical architecture, GEL (Guided English Language), query translation, Snowflake integration, hallucination mitigation.
  4. www.businesswire.com — Slack API integration (upcoming), Gartner recognition, company growth trajectory, customer portfolio.
  5. www.crunchbase.com — Founding year (2017), founders (University of Wisconsin researchers), headquarters (Madison, WI), funding history.
  6. www.g2.com — User ratings, real-world feedback on ease of use, slow loading, limited customization for complex workflows.
  7. www.gartner.com — Gartner Peer Insights recognition, analyst coverage (Emerging Tech mention 2024).