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DESCRIPTION:Click for Latest Location Information: http://dgiq-edw2026.data
 versity.net/sessionPop.cfm?confid=165&proposalid=16397\nBuilding a trusted 
 data ecosystem requires more than dashboards and policies. It requires
  a measurable, repeatable way to evaluate trustworthiness across the enterp
 rise in support of your AI readiness goals. This session presents a real-wo
 rld case study of designing and operationalizing a comprehensive Trusted Da
 ta Score within a large insurance and financial services organization. The 
 score integrates metadata from many platforms to quantify trust across Owne
 rship, Curation, Quality, Protection, and Observability.\n\nAttendees will 
 learn how the scoring model was designed, how the concept was socialized, a
 nd how automation was built to keep the score continuously updated. The ses
 sion will focus on practical implementation steps, organizational adoption 
 strategies, and lessons learned from deploying the approach at scale. This 
 talk is ideal for data governance leaders, stewards, and architects in
 terested in moving beyond conceptual frameworks toward actionable, automate
 d trust measurement.\n\nKey takeaways: \n\n
 A practical blueprint for defining and implementing a measurable Trusted Da
 ta Score.\n
 Methods for integrating and harmonizing metadata across catalog, quality, l
 ineage, and CMDB platforms.\n
 Proven techniques for driving stewardship engagement and aligning organizat
 ional behavior to trust metrics.\n
 Lessons learned from automating trust scoring and embedding it into governa
 nce workflows and dashboards.\n
 Approaches for communicating trust insights to executives in simple, decisi
 on-ready formats.\n\n
DTSTART:20260506T114500
SUMMARY:Building a Trusted Data Score: Lessons From Real-World Enterprise I
 mplementation
DTEND:20260506T122959
LOCATION: See Description
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