Bridge the DQ Dimensions Theory-Practice Gap Using the Open DQ Repository

In today’s AI-driven and data-centric world, organizations are under increasing pressure to ensure their data is accurate, trustworthy, and fit for decision-making. Yet many struggle with fragmented definitions of data quality, inconsistent measurement approaches, and a gap between theory and real-world implementation.
Join Dan Myers, founder of DQMatters and creator of the Open Data Quality Repository, for an engaging introduction to a proven, industry-aligned framework (Conformed Dimensions of Data Quality) that brings clarity, structure, and measurability to data quality.
This session introduces a standardized, objective, and system-independent approach to defining and improving data quality—connecting conceptual frameworks directly to practical techniques used in modern data environments using the Open Data Quality Repository.
What Attendees Will Learn
1. How to Leverage Pre-built Out-of-the-box DQ Metrics
2. How to Avoid Vendor Lock-in While Consolidating DQ Monitoring
3. How to Use Open Architecture to Lower Cost and Increase Flexibility
Topics Covered
o The relationship between: Dimensions, Underlying concepts, Metrics, Rules and Thresholds
o High costs that limit adoption and scalability of DQ tools and ODQ Repo alternative
o Deploying the Open DQ Repository with standard ANSI SQL on any relational database