Data Quality Dimensions

Before any AI or analytics initiative, you need to understand your data quality baseline. This checklist helps you evaluate the four core dimensions.

1. Completeness

Are required fields populated? What percentage of records have missing critical data?

2. Accuracy

Does the data reflect reality? When was it last validated against source systems?

3. Consistency

Do the same entities have the same identifiers across systems? Are definitions aligned?

4. Timeliness

How current is the data? What is the lag between real-world events and system updates?

Using This Checklist

Work through each section with your data stewards. Score each dimension on a 1-5 scale and identify the gaps that will block your analytics goals.