Book Image

Practical Data Quality

By : Robert Hawker
Book Image

Practical Data Quality

By: Robert Hawker

Overview of this book

Poor data quality can lead to increased costs, hinder revenue growth, compromise decision-making, and introduce risk into organizations. This leads to employees, customers, and suppliers finding every interaction with the organization frustrating. Practical Data Quality provides a comprehensive view of managing data quality within your organization, covering everything from business cases through to embedding improvements that you make to the organization permanently. Each chapter explains a key element of data quality management, from linking strategy and data together to profiling and designing business rules which reveal bad data. The book outlines a suite of tried-and-tested reports that highlight bad data and allow you to develop a plan to make corrections. Throughout the book, you’ll work with real-world examples and utilize re-usable templates to accelerate your initiatives. By the end of this book, you’ll have gained a clear understanding of every stage of a data quality initiative and be able to drive tangible results for your organization at pace.
Table of Contents (16 chapters)
Part 1 – Getting Started
Part 2 – Understanding and Monitoring the Data That Matters
Part 3 – Improving Data Quality for the Long Term

Implementing data quality rules

The remainder of this chapter describes the end-to-end process of implementing data quality rules. This process is similar to any other IT implementation in that it has a design stage, a build stage, and a testing stage.

What is unique to data quality implementation work is the need to be ready to iterate. When a design is documented, you can feel that you have full confidence it is completely correct, and then in the build and test phases, you will find that the data requires additional subtleties in the rules that were previously unanticipated.

We will describe the implementation work in the following three sections.

Designing rules

The process of designing a data quality rule starts with the data discovery process outlined in Chapter 5. By the end of Chapter 5, we understood the business strategy and successfully linked it to the data that mattered. We profiled that data and learned about its values and patterns. The rule design phase...