Skip to main content
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 needs to be connected first; once the source is configured, daily discovery jobs take over.

​
What ClarityQ Needs From You

Share the following with your ClarityQ contact:
InputWhat it is
Events tableThe fully qualified path of the warehouse table that holds your events (e.g., my-project.analytics_123456.events_*)
FiltersSQL WHERE conditions used to scope ingestion (e.g., restrict to a single app bundle, exclude staging traffic, drop pre-launch events)
Ignore patternsRegex 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 rulesPatterns identifying which platform-version combinations to include or exclude (e.g., skip beta builds)
Datetime formatThe format your event date column uses, if it’s not the default YYYY-MM-DD

​
What Happens After Setup

1

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.
2

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.
3

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.
4

You review, describe, and approve

Use the Missing Description Wizard to fill in any items still without a description, then approve them.
5

Sync to the Semantic Catalog

Once an event is approved, sync it to the Semantic Catalog so the agent can use it in metrics, segments, and ad-hoc questions.
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.
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.