In Part 1 of this column, I noted that rationalizing, cleaning and maintaining all entity data across your entire enterprise is a daunting prospect. Successful data quality management is a process of aligning your areas of focus for data quality enhancements with the strategic and tactical goals of your business end users. Last month, I focused on the attributes of entity data. This month, I will complete the high-level framework by describing how you can optimize your data quality enhancement efforts by focusing on different quality characteristics.
As a quick reminder, last month I provided an example of a company with a strategic goal to sell more products to existing customers. The entity data attributes most important for achieving the objective were entity identity, individual identity and transactional data for sales, customer service and product development. These three types of data have quite different chronic data quality issues for most companies.
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