eLearningCurve

More and more companies initiate data quality programs and form data stewardship groups every year. The starting point for any such program must be data quality assessment. Yet in absence of a comprehensive methodology, measuring data quality remains an elusive concept. It proves to be easier to produce hundreds or thousands of data error reports than to make any sense of them.

This course gives comprehensive treatment to the process and practical challenges of data quality assessment. It starts with systematic treatment of various data quality rules and proceeds to the results analysis and building aggregated data quality scorecard. Special attention is paid to the architecture and functionality of the data quality metadata warehouse.

• The what, why, when, and how of data quality assessment
• How to identify and use data quality rules for assessment
• How to ensure completeness of data quality assessment
• How to construct and use a data quality scorecard
• How to collect, manage, maintain, warehouse and use data quality metadata