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Data Readiness Index Self-Diagnostic
How to Use This Assessment
The DRI Self-Assessment scores your enterprise's AI readiness across five foundational dimensions. Each dimension contains four questions. Rate each question honestly on a 1-5 scale using the guide below. Keep track of your scores as you complete each section.
Dimension 1 — Data Quality
Accuracy:
Do your source systems produce data that reliably reflects real-world events?
Consider: error rates, duplicate records, mismatched identifiers across POS, e-commerce, loyalty, ERP, and supplier feeds.
(Required.)
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Completeness
: What percentage of critical data fields are consistently populated across your core systems?
Consider: null rates in key fields, missing transaction records, gaps in customer identity linkage, absent inventory events.
(Required.)
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Freshness:
Is data available at the latency required for the AI use cases you are targeting?
Consider: batch vs. near-real-time delivery, SLA compliance on pipelines, known lag between event and availability in the warehouse.
(Required.)
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Consistency:
Are the same entities and measures defined and calculated the same way across all systems?
Consider: mismatched product taxonomies, conflicting customer IDs, inconsistent date and currency formats, divergent KPI definitions.
(Required.)
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1 / 6
17%