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

Summary

This chapter has focused heavily on the difficult first weeks after the approval of a data quality initiative business case. In every data quality initiative I’ve been involved in, those early weeks have not been as productive as I had hoped.

Choosing your third-party partners (both for resources and tools) and hiring the right people in your team will define the success and failure of your initiative. This chapter has outlined what to look for in team members and will hopefully help you to get the right team in place.

We also discussed how to break down the initiative into manageable chunks and to ensure that most, if not all, of the workstreams progress at the right speed.

If the early weeks are successful, the initiative will be well set up to deliver a successful data discovery phase. That is the subject of Chapter 5.