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Competing with High Quality Data: Concepts, Tools, and Techniques for Building a Successful Approach to Data Quality by Rajesh Jugulum

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Chapter 6 Critical Data Elements: Identification, Validation, and Assessment1

6.0 Introduction

The data quality assessment and improvement initiative begins with identifying the data elements that need to be monitored, assessed, and improved from tens of thousands of data elements. The data elements that are selected are called critical data elements (CDEs). In this chapter, we discuss how to identify CDEs, how to validate them, and how to conduct CDE assessment with the help of data quality rules and data quality scores. The techniques proposed in this chapter are useful in the Assess phase of the DAIC approach.

6.1 Identification of Critical Data Elements

6.1.1 Data Elements and Critical Data Elements

Data elements are data attributes used in running a business. For example, the name of a customer is a data element that can be used in account management, marketing, and customer service. From a technical standpoint, a data element is defined as an aspect of an individual or object that can take on varying values among individuals (Herzog et al. 2007).

Critical data elements (CDEs) are defined as “the data that is critical to success” in a specific business area (line of business, shared service, or group function), or “the data required to get the job done.” Note that data that is critical in one business area may not be critical in another. Also note that when identifying CDEs, we often look at reports that may present values derived from underlying data; derived values ...

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