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Configuration Agent

The configuration agent helps you set up your workspace by scanning your data warehouse and configuring the right tables for analytics. Instead of manually mapping event tables, dimension tables, and columns, the agent handles it for you.

What it can do​

  • Scan your warehouse — list schemas and tables, inspect column types and names
  • Identify event tables — recognizes common patterns from vendors like Segment, Snowplow, GA4, and Firebase, as well as custom event tables
  • Identify dimension tables — finds user/account profile tables for enriching your analytics with user-level attributes
  • Map columns automatically — detects timestamp, user ID, and event name columns with high confidence
  • Configure tables — adds event and dimension tables to your workspace with the correct field mappings
  • Trigger indexing — starts indexing after configuration so your data is ready to query

During onboarding​

The first time you set up a workspace, the home page shows a Set up with AI button. Click it to connect your data warehouse and let the configuration agent take over.

Onboarding home page with Set up with AI button

In onboarding mode, the agent works with minimal friction:

  1. Connect your warehouse — provide your data warehouse credentials
  2. Automatic scanning — the agent explores your schemas, identifies event and dimension tables, and maps columns
  3. Auto-configuration — high-confidence tables are configured automatically. The agent asks about ambiguous ones.
  4. Indexing — once configured, indexing starts so your data is ready for analysis
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The agent starts with a minimum viable set of 4-6 event tables and 1-2 dimension tables. You can always add more tables later — getting started quickly is more important than configuring everything upfront.

Configuration agent setup summary with discovered events and next steps

After initial setup​

Switch to the configuration agent at any time using the agent mode selector — the dropdown in the corner of the agent chat input. This is available everywhere the agent appears: the home page, the full-screen agent view, and the sidebar panel. You can also access it directly from the Settings pages.

Agent mode selector showing Analytics and Config options

Outside of onboarding, the agent is more conversational — it asks clarifying questions and requires your confirmation before making changes.

Common use cases:

  • New events in your tracking — you've added new analytical events to your data warehouse and want to pull them into Mitzu
  • New dimension tables — a user profiles or account attributes table was added and you want to use it for breakdowns
  • Reconfigure field mappings — column names or roles have changed and the existing mappings need updating
  • Remove stale tables — deprecated or replaced tables that should no longer appear in the data catalog
  • Explore your warehouse — discover what other schemas and tables are available that you haven't configured yet

What it recognizes​

The agent understands common data warehouse patterns:

  • Vendor tables — Segment tracks, Snowplow events, GA4 event tables, Firebase analytics
  • Event table signals — tables with _events suffix, or names like tracks, pages, sessions
  • Dimension table signals — tables with _profiles suffix, or names like users, accounts
  • Skips automatically — tables with deprecated, tmp, staging, backup, or archive in the name

Permissions​

  • Admins can discover, configure, and remove tables
  • Non-admins can discover tables and get recommendations, but cannot make changes — the agent presents its suggestions for an admin to implement