13 Data Quality Management Concepts and Techniques | DAMA DMBOK - Data Management Body of Knowledge

Bad data = bad decisions. In this talk, we deep dive into Data Quality Management as outlined in the DAMA DMBOK (Data Management Body of Knowledge). Learn how to define, measure, and improve data quality using proven frameworks and tools. ✅ What you’ll learn: Dimensions of Data Quality (accuracy, completeness, timeliness, etc.) Key roles and responsibilities in Data Quality Management Techniques for profiling, monitoring, and cleansing data Root cause analysis and remediation approaches How to embed DQ into enterprise data governance 🎯 Based on: DAMA DMBOK v2 🎓 Ideal for: Data stewards, quality analysts, architects, and governance leaders 📊 Industries: Finance, healthcare, retail, public sector #DataQuality #DataManagement #DAMA #DMBOK #DataGovernance #DataCleansing #DQMetrics #DataProfiling #EnterpriseData #TrustedData #DataQualityFramework