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Databases & DWH

Pragmatic integration for SQL databases and data warehouses

Typical systems

  • PostgreSQL, MySQL, MSSQL
  • data warehouses (e.g. Snowflake, BigQuery, Redshift)
  • reporting-oriented SQL backends

Pragmatic first

If direct access is possible

  • start with the custom database approach
  • validate first read-only use cases
  • deliver fast answers on structured data questions

If tighter control is needed

  • use Dataset Manager (SQL)
  • leverage automatic schema introspection
  • explicitly allow/limit fields
  • define stable SQL snippets as functions

If direct access is not possible

  • provide scheduled exports (CSV/SQL dumps)
  • start with Dataset Manager or data-pool-adjacent workflows

Which path when?

  • operational live queries -> direct DB access
  • repeatable analytics -> Dataset Manager
  • constrained infrastructure -> export-first approach

Practical 3-step start

  1. pick 1-2 tables with clear business questions
  2. apply read-only setup and query limits
  3. validate responses with business owners before scaling

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