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Data & AI readiness

A clearer starting point for your data journey.

Use five practical questions to review source ownership, data quality, metric definitions, permissions and operational readiness.

A practical reflection worksheet, not a certified maturity score. Five questions, no email required. Your responses stay in this page and are cleared when you leave or reload.

1. Can you identify who owns each critical data source?

Look for a person or team that can approve definitions, access and changes.

2. Are quality and freshness checked before people use the data?

A successful pipeline run is not the same as complete, timely and correct data.

3. Do teams use agreed definitions for important metrics?

Check the calculation, time period, exclusions and owner of a KPI.

4. Are access, correction and deletion rules carried into derived data?

Include warehouses, reports, search indexes and model inputs in the review.

5. Is there a tested owner and recovery path when something fails?

Look for monitoring, an escalation route and a rehearsed recovery procedure.