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

Data quality in the wider context of data governance

Before explaining all the elements of a data quality initiative in detail, it is important to recognize that data quality is ideally implemented alongside a data governance initiative.

It is possible for data quality to be implemented as a standalone activity, but there are benefits from complementary activities related to data governance. The following sections outline the various aspects of data governance.

Data governance as a discipline

The focus of this section is mainly on data governance, but it is important to explain that data governance is actually part of a wider concept called “data management.” Data management covers all aspects of how data is treated in an organization. For example, data management includes the following:

  • Data quality
  • Data privacy
  • Master data management
  • Data warehousing and business intelligence

DAMA UK offers a complete explanation of data management...