How It Works
This page explains the mechanics behind the Export Operation: the asset types it supports, how containers are selected, where the data lands in your enrichment datastore, how the operation runs asynchronously, and what happens when you re-run it.
Asset types
Each Export Operation captures one asset type per run, chosen at the modal's Choose step:
| UI label | API value | Output table suffix |
|---|---|---|
| Anomalies | anomalies |
_export_anomalies |
| Quality Checks | checks |
_export_checks |
| Field Profiles | profiles |
_export_field_profiles |
The exported columns differ by asset type. See Export Schema for the full column list of each.
Container selection
You decide which containers (tables, files, or views in the source datastore) the export covers:
| Selection mode | What gets exported |
|---|---|
| All | Every container in the source datastore at the time the operation runs. When attached to a schedule, future containers are included automatically as they are profiled. |
| Specific | Only the containers you select manually. Selection is stable across re-runs. |
| Tag | Every container that carries the selected tag(s) at the time the operation runs. New containers tagged later are picked up by future runs. |
The three modes are mutually exclusive: pick one per operation.
Where the data lands
The exported data is written as a table in the linked enrichment datastore, not a downloadable file. The table name follows a fixed pattern:
_<sanitized-datastore-name>_export_<asset>
<sanitized-datastore-name>is the source datastore's name with every non-alphanumeric character replaced by_, then lowercased.<asset>isanomalies,checks, orfield_profiles(note: the Field Profiles asset uses thefield_profilessuffix in the table name even though the API enum value isprofiles).
Examples for a source datastore named "Acme Sales 2024":
- Anomalies table →
_acme_sales_2024_export_anomalies - Quality Checks table →
_acme_sales_2024_export_checks - Field Profiles table →
_acme_sales_2024_export_field_profiles
Re-runs overwrite
Running an export a second time for the same datastore and asset type replaces the existing table. The table is not appended to or versioned. If you need point-in-time snapshots, schedule recurring exports and have your downstream pipeline copy the table elsewhere after each run completes.
Async execution model
The Export Operation runs asynchronously:
- You trigger the export. The platform validates the request, creates an Operation record with
result = queued, and enqueues the work. The trigger call returns immediately. - The operation moves to
result = running. The dataplane receives the request, computes the export payload, and writes the table to the enrichment datastore. -
When the write completes, the operation transitions to one of:
Result Meaning successAll containers exported. partialSome containers exported, others failed. Inspect the operation message for details. warningExport completed but with non-fatal issues. failureThe export did not complete.
The operation is visible on the source datastore's Activity tab from the moment it is queued. The page auto-refreshes as the result changes.
Scheduling
An Export Operation can be scheduled to run on a recurring cadence. Schedules support:
- Hourly / Daily / Weekly / Monthly / Custom Cron frequencies
- Any IANA timezone (e.g.
America/New_York,Europe/Paris,Asia/Tokyo). The default is UTC. - Automatic Daylight Saving Time handling: a 9:00 AM job in
America/New_Yorkruns at 9:00 AM local time year-round.
Deactivating a schedule keeps its cron expression. Reactivating it later resumes the same schedule without re-entering anything.
See Schedule Export for the modal walk-through.
Re-running a completed export
Any user with Editor permission on the source datastore can re-run a previously completed Export Operation. The re-run uses the original operation's parameters (asset type, container selection, include_masked flag) and produces a fresh operation. The new operation overwrites the existing enrichment table on completion.
Re-runs are allowed only after the original operation has finished: attempting to re-run an in-progress operation produces an error.