> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clarityq.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Setting Up Your Event Catalog

> How to connect ClarityQ to your product analytics events and run the initial discovery.

The Event Catalog reads from a single table in your data warehouse — the one your analytics platform writes events to. Setting it up tells ClarityQ which table to read, which rows to keep, and which events or properties to ignore.

Setup is done with ClarityQ during onboarding. Your [data warehouse](/get-started/connect-your-data-warehouse) needs to be connected first; once the source is configured, [daily discovery jobs](/context-layer/event-catalog/daily-discovery-jobs) take over.

## What ClarityQ Needs From You

Share the following with your ClarityQ contact:

| Input               | What it is                                                                                                                                                                                     |
| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Events table**    | The fully qualified path of the warehouse table that holds your events (e.g., `my-project.analytics_123456.events_*`)                                                                          |
| **Filters**         | SQL `WHERE` conditions used to scope ingestion (e.g., restrict to a single app bundle, exclude staging traffic, drop pre-launch events)                                                        |
| **Ignore patterns** | Regex patterns for events, parameters, or user properties you don't want catalogued — useful for internal debug events, deprecated names, or fields you'd rather keep out of the agent's reach |
| **Version rules**   | Patterns identifying which platform-version combinations to include or exclude (e.g., skip beta builds)                                                                                        |
| **Datetime format** | The format your event date column uses, if it's not the default `YYYY-MM-DD`                                                                                                                   |

## What Happens After Setup

<Steps>
  <Step title="Initial discovery runs">
    ClarityQ scans the events table, identifies every distinct event name, parameter, and user property in the configured window, and creates entries in the catalog.
  </Step>

  <Step title="Items show up in the Event Catalog">
    The Events, Common Parameters, and User Properties tabs populate. Everything starts in `Pending` approval status with `Active` data status.
  </Step>

  <Step title="AI fills in known descriptions">
    For supported platforms, ClarityQ pre-fills descriptions where it recognises the event or property. The rest are left for you to describe.
  </Step>

  <Step title="You review, describe, and approve">
    Use the [Missing Description Wizard](/context-layer/event-catalog/missing-description-wizard) to fill in any items still without a description, then approve them.
  </Step>

  <Step title="Sync to the Semantic Catalog">
    Once an event is approved, [sync it to the Semantic Catalog](/context-layer/event-catalog/syncing-events-to-the-semantic-catalog) so the agent can use it in metrics, segments, and ad-hoc questions.
  </Step>
</Steps>

<Tip>
  If your events table is the GA4 BigQuery export, ClarityQ already ships with descriptions for the standard GA4 events (`session_start`, `screen_view`, `first_visit`, and so on) and the common GA4 parameters and user properties — they come back pre-filled, leaving you only your custom events to describe.
</Tip>

<Note>
  The daily discovery job looks at a rolling two-day window, so newly-instrumented events appear within a day. If you need to backfill an older period — for example, to catch events from a launch that happened months ago — ask ClarityQ to run a one-time backfill against the date range you care about.
</Note>