Channels ▼


Dr. Dobb's Agile Newsletter

Book Review: Journey to Data Quality

From a theoretical point of view Journey to Data Quality, by Y.W. Lee et. al, is a great read which I highly suggest to all data professionals and to senior IT management. The book starts with a discussion of the cost/benefit of data quality, something which should be an eye-opener to any IT professional -- some estimates claim that business is impacted by poor quality data by as much as 8-12 percent of revenue. Chapters 3 through 5 describe how to assess the quality of data, the first step in understanding where to invest effort for addressing the data problems that your organization faces. Chapter 6 describes the root causes of data quality problems and Chapter 7 works through a case study within a health-care organization. Chapter 8 is arguably the most valuable one within the book, arguing that information should be managed as a product, not just as a by-product of systems, a philosophy which motivates quality practices within an organization. Chapter 9 overviews a type of model known as an information product (IP) map, a combination of a flow chart and data-flow diagram (DFD). Chapter 10 describes another case study, Chapter 11 summarizes the main points of the book, and Chapter 12 provides a vision for succeeding at the long journey ahead of you.

From a practical point of view this book was a bit of a disappointment. Although there is a lot of advice which organizations can use to improve their overall data quality processes, most of them seem to be based on increasing the overall complexity of your software process and the supporting bureaucracy. There was no mention of testing at all. Call me old fashioned, but a comprehensive testing strategy should be part of any quality program that you embark on. Without a doubt this book is a good start on the path to data quality, but it will only get you so far.

Journey to Data Quality

Y.W. Lee, L.L. Pipino, J.D. Funk, and R.Y. Wang.

MIT Press, 2006


Related Reading

More Insights

Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

Dr. Dobb's encourages readers to engage in spirited, healthy debate, including taking us to task. However, Dr. Dobb's moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing or spam. Dr. Dobb's further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.