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

An overview of the data discovery process

Data discovery is the process where an organization obtains an understanding of which data matters the most and identifies challenges with that data. The outcome of data discovery is that the scope of a data quality initiative should be clear and data quality rules can be defined.

This starts with understanding the strategy of your organization, the objectives of key stakeholders, and crucially, what is getting in the way of fulfilling these. It is important to ask stakeholders to talk about this holistically and not to filter their answers, based on what they think might be data quality related. It is very common for issues to appear to have little to do with data, but when an investigation takes place, a link to data quality is uncovered. Clearly, not every problem will have a data quality root cause, but it is important to have the chance to form your own expert opinion.

Once the strategy and objectives are well understood, it is time...