Here’s a workflow for assessing and changing a data asset’s certification (e.g. to Certified).
- Retrieve context: Retrieve the entire context of that metadata (e.g. the data asset’s full profile).
- Check completeness: Check the completeness of that context.
- Queue exceptions: If expected or required context is missing, add the asset to an exception queue for human review.
For example, if a data asset is Certified but has no description or owner, ask someone to review whether this is correct. While the asset is being reviewed, you could also remove the certified status.
Maintain a minimum acceptable standard for certified metadata.
Continuous validation of metric calculations
Ensure that calculations are accurate and identify problems.
Automatically assign a freshness status to assets
Avoid accidental reuse of stale assets.
Automated quality control of data pipelines
Avoid propagation and use of poor quality data.