This session covers the use and output of Gartner’s AI-Ready Data Toolkit, which includes practices for both structured and unstructured data. The process develops metrics that “stack” as you progress from POCs to multicontext data use, operationalization and production support. The session also explains how to customize the toolkit with your own thresholds and readiness analysis.

D&A leaders struggle to prioritize and justify data management spend, especially amid cloud-driven cost unpredictability. Value stream analysis links data production to direct and indirect business outcomes, driving quantifiable benefits. This session will link core research on cost management and FinOps with a means of using active metadata to measure value resulting in holistic cost optimization.

Most metadata in 2025 will remain passive in approaches with stats, reports, schema and business-developed glossary terms. Yet, organizations must grow their maturity in metadata management. We start with traditional metadata techniques — passive. With AI undergoing confidence issues and the demand to reduce risk, grow AI confidence and provide data assurance, active metadata becomes key.

This session covers the use and output of Gartner’s AI-Ready Data Toolkit, which includes practices for both structured and unstructured data. The process develops metrics that “stack” as you progress from POCs to multicontext data use, operationalization and production support. The session also explains how to customize the toolkit with your own thresholds and readiness analysis.