Data Mining Book Review: Decision Management Systems

DMSI recently read the last book from James Taylor, Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics. As a data miner, I was interested by the subtitle of the book. Although, the book is really well written, I’m a bit disappointed regarding the content for someone in analytics. I was expecting real methodologies and examples to move from analytics to actions in the company. How to successfully apply predictive analytics in the industry. The book only partly answers this question and gives mainly examples of business rules and how they are applied in companies.

If you come from the business side (e.g. C-level), the book may be interesting but the explanations about predictive analytics are quite light and you won’t see all benefits of these techniques in the company. I know that the main focus of the book is not about teaching analytics. It seems also not to be about filling the gap between analytics and action. I’m thus a bit confused about the real objective of the book. It is also explaining concepts at a very high level of abstraction. It is thus not directly usable in practice.

The book is divided in three parts. In the first part, James explains what are DMS and why they are useful for the company. The second part focuses on building these DMS. The third part is about the enablers (people, processes and technology), i.e. the aspects that will allow such DMS to be a successful initiative. Personally, I found the book very interesting starting from chapter 6 (Design and Implement Decision Services). The topic of fraud detection and prevention is very well studied throughout the book.

A very strange choice has been made to repeat in full text the expression Decision Management Systems hundreds of times. It thus makes the reading sometimes a bit tiring. The simple use of the abbreviation DMS would have solved this issue. To conclude, I found the book interesting and well written. However, keep in mind that it is written with a very high level of abstraction. You will thus have a clear understanding of the domain, but no practical advices.

Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics


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Comments Icon6 comments found on “Data Mining Book Review: Decision Management Systems

  1. Also, thanks for the review! I was thinking about getting the book but if it’s what you say then I’ll try and find a better one

    Keep up the great posts!

  2. Sandro

    Thanks for taking the time to read and review Decision Management Systems. I appreciate your feedback and I am glad you found the chapters from chapter 6 (Design and Implement Decision Services) useful. There is a trade-off between the length of a book and completeness and there are a variety of free resources on the Decision Management Solutions website in addition that can provide additional detail.

    The heart of decision management is filling the gap between analytics and action. While some of the techniques and examples are clearly focused on business rules, rather than analytics, the overall framework works for both. Business rules are a technology of real value to data miners and analytic professionals because business rules technology is such a useful platform for rapid deployment of models.

    We’ve had great success on projects using the decision management approach with data miners very pleased in its usefulness in getting a consistent problem understanding with the business and in getting models quickly deployed. Decision Discovery makes it easier to tell where analytics will make a difference in concert with the business team and what analytics will be required. The construction of Decision Services to automate these decisions (using analytics and business rules in particular) and ongoing Decision Analysis ensures that models (and rules) don’t go stale and that the value of analytics grows over time rather than declining. I’ve been told it makes for “business friendly” data mining, and liked that title so much that’s what I’ve called my upcoming workshop at Predictive Analytics World SF in March.

    And spell, I hope you will reconsider.


  3. @James: Thanks for your comment. I’m sure several readers will find (or already found) it interesting. No doubt it will have its audience. Don’t get me wrong, the book contains excellent material. I just didn’t find what I was looking for.

    Maybe I was expecting something much more usable since I often read your posts on Information Management and find them really useful (that’s the reason why I bought the book)! Starting from your posts on Information Management, I was expecting something else, and I read the book with this expectation in mind.

    Thanks for your nice posts on Information Management!

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