Data and analytics · 5 apps
AI assistants for cloud data warehouses
AI assistants can answer business questions straight from your cloud data warehouse: revenue by region, late orders, active accounts. mcpbizapps makes that safe by letting each role read only approved views and agreed tables, applying row limits by person, checking query size before anything runs and logging the query behind every answer. Nobody needs their own warehouse login, and nothing is written to your tables.
Every app is available
Cloud data warehouses apps you can connect
Each app gets the same sign-in, roles, previews, approvals and audit log. We connect each one for your team in a guided pilot.
- Available
Snowflake
Cloud data platform where companies store, share and query analytics data in databases, schemas and views, with compute run by virtual warehouses.
See what it can do - Available
Google BigQuery
Google Cloud's serverless data warehouse, organized into projects and datasets, where teams run analytics over very large tables without managing servers.
See what it can do - Available
Databricks
Data and AI platform built on the lakehouse, where teams govern tables in Unity Catalog and run notebooks, jobs and SQL warehouses.
See what it can do - Available
Amazon Redshift
Amazon's cloud data warehouse, run as provisioned clusters or serverless workgroups, used for reporting on large volumes of structured data.
See what it can do - Available
Microsoft Fabric
Microsoft's analytics platform that brings lakehouses, warehouses, data pipelines and Power BI together on one copy of data in OneLake.
See what it can do
Use cases
What teams use it for
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Governed text to SQL for analysts
Analysts ask in Claude or ChatGPT and get an answer with the query shown. Queries read only approved views, so the numbers match the reports the data team already maintains.
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Finance figures from approved marts
Finance teams ask about revenue, expenses and balances from the finance schemas your data team signs off, with row limits by entity or cost center, instead of exporting tables into spreadsheets.
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Warehouse spend and usage
Data leaders ask which warehouses, workgroups or projects used the most compute and where spend grew, then prepare a pause or limit for someone to approve.
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Data freshness and pipeline checks
Analysts and engineers ask which jobs, pipelines or scheduled queries failed overnight and which reporting tables are stale, before anyone presents a number from them.
Real questions
Questions people ask in Cloud data warehouses apps
A sample from the app pages. Each answer comes live from the app, for the people allowed to see it.
- “What was net revenue by region last quarter, using the approved revenue view in the finance_reporting schema?”
- “Show weekly active accounts for the last 12 weeks from the approved product usage view.”
- “How many DBUs did each SQL warehouse use last week, and which teams drove the increase?”
- “How many RPU hours did each serverless workgroup use this month?”
- “Which plants missed their output target last week, according to the operations semantic model?”
Governance
What to control in Cloud data warehouses
The risk in this category is breadth. One warehouse connection can reach payroll, customer details and revenue at once, and one careless query can scan billions of rows. mcpbizapps keeps each role on approved views, respects the masking and row policies already in the warehouse, adds row limits where none exist, estimates query size before running and uses compute you size for questions. Any change, such as pausing a warehouse, is previewed and approved, and the audit log records the exact query behind each answer.
- Roles per tool
- View only switch
- Preview first
- Approval rules
- Audit log
Cloud data warehouses questions
Can an AI assistant write to our tables?
No. Connections in this category use read-only warehouse roles, and mcpbizapps rejects statements that insert, update, delete or drop before they reach the warehouse. The only changes on offer are operational ones, like pausing a warehouse, and those need confirmation and approval.
How is this different from giving analysts a SQL client?
A SQL client gives each person a login and full reach within it. mcpbizapps gives each role a short list of approved views, row limits and query size limits, and records every question and query against a name. People who do not write SQL can ask too.
Do answers match our existing dashboards?
They can, because the assistant reads the same approved views and marts your dashboards use. During the pilot we choose those views together and describe each column, so a question about net revenue means the same thing in a chat as in a report.
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Bring your Cloud data warehouses apps into your AI assistant
In 30 minutes we show an assistant looking up and preparing work in your kind of app, with the approval and the audit trail. Bring the questions your team asks every week.