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After you connect your data warehouse, the setup wizard directs you to the Table Catalog. From here, you add the tables you want ClarityQ to catalog.

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Adding Tables

Click Add Tables in the Table Catalog to open the table selection wizard. The wizard walks you through three steps:
1

Select tables

Browse your warehouse’s schemas and choose the tables you want ClarityQ to catalog. You don’t need to add all tables — focus on the ones relevant to your analytics.
2

Define mandatory filters (optional)

Set SQL WHERE conditions that are automatically applied to every query ClarityQ runs against the selected tables. Useful for scoping to a specific product, excluding deleted records, or filtering out stale data. See Mandatory Filters below.
3

View added tables

See a summary of the tables that were added to your catalog.
The Table Catalog page then displays the tables you added, along with their discovered schemas, columns, and metadata.
Your organization’s admin sets a maximum number of tables that can be added to a product’s context. The agent only uses tables that are in the Table Catalog — tables in your warehouse that haven’t been added are invisible to ClarityQ.
Start with your most important tables — the ones your team queries most often. You can always add more tables later by clicking Add Tables again.

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What Happens During Discovery

When you add tables, ClarityQ runs a discovery workflow for each one:
  1. Schema extraction — Queries your warehouse for the table’s structure, columns, data types, and constraints
  2. Column value sampling — Fetches up to 50 distinct values for categorical columns
  3. Metadata collection — Captures row counts, table size, partitioning, clustering, and timestamps
  4. AI description generation — Automatically suggests descriptions for tables and columns that don’t have one
Discovery runs in parallel across multiple tables. Each table’s state is tracked independently — you’ll see an In Progress spinner while it’s running, a Completed checkmark when done, or an Error indicator if something went wrong.

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Mandatory Filters

Mandatory filters let you define SQL WHERE conditions that are automatically applied to every query ClarityQ runs against your tables. They’re useful for scoping your data — for example, restricting to a specific product, excluding deleted records, or filtering out stale data. Examples:

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When to use them

  • You have multi-tenant tables and want ClarityQ to only see data for your product
  • You need to exclude test data, deleted records, or irrelevant rows
  • You want to limit the date range ClarityQ queries to avoid scanning historical data you don’t need

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How they work

  • Set during table selection — The table selection wizard lets you define mandatory filters that apply to all newly added tables.
  • Edit per table — After setup, you can adjust filters for individual tables from the table settings.
  • Validated before saving — ClarityQ runs a dry-run validation against your warehouse to make sure the filter syntax is correct.
  • Enforced automatically — Every query ClarityQ generates for a filtered table includes these conditions in the WHERE clause. Users don’t see or need to think about them.
Mandatory filters set during table selection apply only to newly added tables. Existing tables are not affected — edit their filters individually from the table settings.

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Table Settings

After a table is cataloged, you can configure it from the table settings:
  • Table type — Classify the table (Events, Fact, Dimension, Lookup, Aggregate, Raw Data). This affects how ClarityQ uses the table.
  • Mandatory filters — Edit the SQL WHERE conditions for this specific table.
  • Analytics engine — For Events tables, specify the analytics platform (e.g., GA4) to enable platform-specific enrichment.
  • Descriptions — Edit table and column descriptions, or accept AI-generated suggestions.

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Reviewing Tables and Columns

After discovery, tables and columns start in Pending status. Review them to confirm they’re accurate:
  • Approve tables and columns you’ve reviewed
  • Hide columns that are irrelevant or sensitive — they won’t appear in the catalog or be used by the agent
  • Edit descriptions to add business context that helps ClarityQ understand what the data means