Data quality is one of the most difficult challenges for nearly every business, IT organization, and BI program. The most common approach to data quality problems is reactive—a process of fixing problems when they are discovered and reported. But reactive data quality methods are not quality management; they are simply quality maintenance—a never-ending cycle of continuously fixing defects but rarely removing the causes. The only proven path to sustainable data quality is through a comprehensive quality management program that includes data profiling, data quality assessment, root cause analysis, data cleansing, and process improvement.
BI, MDM, and data governance program and project managers and practitioners; data stewards; data warehouse designers and developers; data quality professionals
Module One: Data Quality Basics
Module Two: Profiling Data
Module Three: Assessing Data Quality
Module Four: Fixing Data Quality Defects
Module Five: Preventing Data Quality Defects
Module Six: Summary and Conclusion
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