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)
1
Part 1 – Getting Started
6
Part 2 – Understanding and Monitoring the Data That Matters
10
Part 3 – Improving Data Quality for the Long Term

Part 3 – Improving Data Quality for the Long Term

As soon as the data quality rules and reports uncover the real data quality position, organizations want to take action to correct it. This part explains how to do that successfully.

However, organizations are often tempted to eliminate bad data through a one-off exercise. This part explains how to ensure that the initial remediation activity is maintained as part of the day to day business activities of the organization.

Once you have completed this final part of the book, you will understand the whole data quality process end to end – from identifying that they have a problem, all the way to correcting the data the long term. You will know which best practices to follow and which common mistakes to avoid.

This part comprises the following chapters:

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