COMPEL Glossary / data-readiness-assessment
Data Readiness Assessment
A data readiness assessment is a structured evaluation of an organization's data ecosystem to determine its fitness for AI transformation, covering data quality metrics, data lineage documentation, metadata management maturity, access governance policies, storage and compute infrastructure scalability, and data team capabilities.
What this means in practice
The assessment produces a data readiness scorecard that identifies specific gaps that must be addressed before AI initiatives can succeed, preventing the common pattern of launching AI projects on data foundations that cannot support them.
Why it matters
Data quality and availability problems are the most common cause of AI project failure, yet organizations frequently skip rigorous data assessment in their eagerness to deploy AI. A structured data readiness assessment prevents wasted investment in AI initiatives built on inadequate data foundations and provides the evidence base needed to justify data infrastructure investments to leadership.
How COMPEL uses it
Data readiness assessment is a core activity of the Calibrate stage, producing baseline evidence that informs the transformation roadmap designed during the Model stage. The AITM-DR micro-credential validates competency in conducting these assessments using the COMPEL data readiness framework. Assessment results feed directly into the 18-domain maturity model scoring for data management and data infrastructure domains.
Related Terms
Other glossary terms mentioned in this entry's definition and context.