Emerald Isle Consulting
Emerald IsleConsulting
Free · 5 minutes

Data Foundation Scorecard

Ten questions across five dimensions. See how ready your data foundation is for production AI, and where the biggest gaps are.

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Data Quality

Whether the numbers are right, and whether anyone measures it.

01When two reports disagree, how quickly can you find out why?
02Do you measure data quality on your most critical fields?

Documentation

Whether what your data means is written down, or lives in people's heads.

03Is there a business glossary and data dictionary for your core systems?
04If a key engineer left tomorrow, could someone else explain how your core data is produced?

Lineage

Whether every number can be traced to its source, and changes traced to their impact.

05Can you trace a number in an executive or regulatory report back to its source systems?
06When a source system changes, do you know which reports and models are affected?

Access & Security

Whether the right people can get to the data quickly, and sensitive data is controlled.

07How long does it take an analyst or data scientist to get approved access to the data they need?
08Are sensitive fields (personal, claimant, and medical data) classified and controlled?

AI Consumability

Whether a model could actually use your data today, without heavy manual work.

09Could a model consume your core data today without a manual extract-and-clean step?
10How much of your key information sits in documents machines can't read (adjuster notes, estimates, PDFs)?
0 of 10 answered

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