Developing a Data Quality and Integration Strategy
Data transformation, cleansing, and integration is the most difficult part of a business intelligence project. A comprehensive approach that carefully considers both the quality expectations and the quality of the source system data helps to bring this activity to a manageable level. This session explains how to establish data quality expectations, the importance of data profiling for understanding and proactively addressing data quality deficiencies, and how to develop a strategy that employs these in planning the data integration activities.
What you will learn:
- How to establish data quality expectations
- How to understand the existing data quality and determine needed actions
- Options for addressing data quality deficiencies within the data integration processes
- Key components of a data quality and integration strategy