Data Quality: The Field Guide

by Thomas C. Redman, Mike Daugherty, Michael Daugherty

Can any subject inspire less excitement than "data quality"? Yet a moment's thought reveals the ever-growing importance of quality data. From restated corporate earnings, to incorrect prices on the web, to the bombing of the Chinese Embassy, the media reports the impact of poor data quality on a daily basis. Every business operation creates or consumes huge quantities of data. If the data are wrong, time, money, and reputation are lost. In today's environment, every leader, every decision maker, every operational manager, every consumer, indeed everyone has a vested interest in data quality.
Data Quality: The Field Guide provides the practical guidance needed to start and advance a data quality program. It motivates interest in data quality, describes the most important data quality problems facing the typical organization, and outlines what an organization must do to improve. It consists of 36 short chapters in an easy-to-use field guide format. Each chapter describes a single issue and how to address it.
The book begins with sections that describe why leaders, whether CIOs, CFOs, or CEOs, should be concerned with data quality. It explains the pros and cons of approaches for addressing the issue. It explains what those organizations with the best data do. And it lays bare the social issues that prevent organizations from making headway. "Field tips" at the end of each chapter summarize the most important points.
Allows readers to go directly to the topic of interest
Provides web-based material so readers can cut and paste figures and tables into documents within their organizations
Gives step-by-step instructions for applying most techniques and summarizes what"works"

Hardcover

First published November 30, 2000

Reviews

[Emily · Rating 5 out of 5]

This is a primer for data quality analysts. Data quality is important and these days, though some corporations have a data quality team, most still don’t!

Not as useful for data analysis, but more if you have the responsibility of monitoring data quality and having structured ways of determining its current quality.

[Eric Wisdahl · Rating 2 out of 5]

I started Data Quality: The Field Guide after seeing it mentioned in a few other texts which I have read on the subject of Data Quality. I have become more and more interested in this subject over the past few years and was hoping to find another great book that I could learn from and potentially share as an introduction level text to others who might also be interested in this area. Data Quality: The Field Guide attempts to reach out in quick hit chapters and focus in on and explain a single topic. Although the single topic per chapter sounds like a good way of working through the various topics, there seems to be something lacking. It is as if each topic is discussed at a bit to high of a level and in to generic of terms to find actionable items to follow. The background information is good, and there were a lot of really good points and useful explanations, but the information might not be enough in and of itself to allow the user to put together a plan for identifying and enacting improvements in data quality. Perhaps the text hasn't aged particularly well (it was written in 2000), or perhaps I was expecting something other than what was delivered, either way I don't know that this is the right introductory book for someone looking to break into the subject.