A quick google search will show that data quality metrics involve all sorts of categories.
Completeness, consistency, conformity, accuracy, integrity, timeliness, continuity, availability, reliability, reproducibility, searchability, comparability, and probably ten other categories I forgot to mention all relate to data quality.
So what are the right metrics to track? Well, we’re glad you asked.
Take a look and let us know what other metrics you think we need to add!
- Metric 1 – Null Counts
- Metric 2 – Schema Changes
- Metric 3 – Data Lineage
- Metric 4 – Pipeline Failures
- Metric 5 – Pipeline Duration
- Metric 6 – Missing Data Operations
- Metric 7 – Record Count in a Run
- Metric 8 – Tasks Read from a Dataset
- Metric 9 – Data Freshness