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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 2 The Data Quality Operating Model1

2.0 Introduction

As mentioned in Chapter 1, the core purpose of the DQ program is to satisfy various requirements that ensure the data is fit for its intended purpose and that it is of high quality. In order to satisfy these requirements, we must have a systematic DQ program that can be applied to various DQ-related projects. The data quality program structure, objectives, management routines, and portfolio of projects need to be focused on building and institutionalizing processes and project results that drive business value. This chapter describes the building of such a comprehensive approach and methodology (referred to as the data quality operating model, or DQOM), which allows us to understand the current state of data quality, organize around information critical to the enterprise and the business, and implement practices and processes for data quality measurement.

2.1 Data Quality Foundational Capabilities

The process of building and strengthening the data quality program requires a concerted effort across business, technology, operations, and executive teams. The focus throughout is to continuously build, enhance, and extend the DQ capabilities across the organization. Once ­implemented, these capabilities constitute a steady-state operating environment that actively defines, manages, measures, and improves the quality of the data that is critical to key business processes throughout the enterprise. In the process of ...

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