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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 5 Statistical Process Control and Its Relevance in Data Quality Monitoring and Reporting

5.0 Introduction

As we have repeatedly mentioned, one of the most important aspects of the data quality operating model (DQOM) is providing a monitoring and control mechanism for critical data elements (CDEs) or process outputs. The monitoring component is useful in the Assess and Control phases, and the control component is useful in the Control phase of the DAIC approach. In this chapter, we discuss statistical process control (SPC) in detail and demonstrate how it can be used in implementing the DAIC approach. Additional uses of SPC include providing a statistical basis to determine business thresholds or specifications. Readers are encouraged to read Chapter 8 to understand how this can be done.

5.1 What Is Statistical Process Control?

Statistical process control is a method for measuring and controlling processes by using numerical facts. Controlling a process means reducing the process variability by clearly distinguishing the controllable variation (or assignable variation) and the uncontrollable variation (natural or chance) of the process. So we can say that the aim of SPC is to understand the variation associated with processes and data elements. Usually, the variation is measured against customer expectations or specifications. Any deviation from the customer expectation is undesirable, and this makes variation the enemy of quality. As discussed in Chapter 1, reducing ...

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