Export Operation Introduction

The Export Operation lets you capture data-quality artifacts that the platform produces (anomalies, quality checks, and field profiles) and write them as tables to your linked enrichment datastore. Once the export finishes, the captured data is queryable like any other table in that datastore, ready for BI tools, scheduled reports, governance dashboards, or audit trails.

What you can export

Each Export Operation captures one asset type per run:

• Anomalies: every anomaly the platform has identified on the selected containers (active, acknowledged, resolved, invalid, duplicate, discarded).
• Quality Checks: every quality check defined on the selected containers, including the rule type, scope, current pass/fail status, and the first and last times the check produced a result.
• Field Profiles: the most recent statistical profile of each field on the selected containers (completeness, distinct values, summary statistics, histograms, and more).

Why this matters

The Export Operation turns the platform's in-memory quality state into durable, queryable data:

• Operational reporting: connect BI tools (Looker, Power BI, Tableau) to the exported tables instead of polling the API.
• Governance and audit: schedule recurring exports to keep a time-series record of quality artifacts in your data warehouse.
• Cross-system analysis: join exported quality data with your business tables to correlate anomalies with downstream impact.

How it runs

Triggering an Export Operation enqueues the work; the platform processes it asynchronously and writes the result to the enrichment datastore. The table appears within a few minutes. You can also schedule recurring exports in any IANA timezone.

Next Steps