We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Data Mining Book Review: Decision Management Systems
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Decision Management > Data Mining Book Review: Decision Management Systems
Book ReviewDecision ManagementPredictive Analytics

Data Mining Book Review: Decision Management Systems

SandroSaitta
SandroSaitta
3 Min Read
Data Mining Book Review: Decision Management Systems
Illustrative image generated with OpenAI gpt-image-1.
SHARE

I 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 disapointed 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 books only partly answer 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 make 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.

More Read

The Quiet-Eye Period
The Quiet-Eye Period
How Big Data Will Change People Management Forever
How are Italy and Performance Management Similar?
Advocate of Analytics – Economist Paul A. Samuelson (1915-2009)
Simple Methods and Ensemble Forecasting of Elections

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

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article's core relationship is workload-by-workload decision-making for cloud migration, where s
Which Workloads Should Move to the Cloud?
Cloud Computing Exclusive IT
Flat editorial illustration: The article positions data governance as a strategic board-level concern rather than a purely techni
Why Data Governance Is Becoming a Board-Level Business Priority
Big Data Exclusive Policy and Governance
Flat editorial illustration: The article argues that data annotation quality should be measured by inspectable gold sets, written
The Top Data Annotation Companies Are Separated by Proof of Quality, Not Headcount
Big Data Exclusive
Flat editorial illustration: The article's core relationship is the gap between raw bank-feed records and reliable subscription i
Subscription Trackers Have a Transaction Data Problem
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Social Media Data and what analysts can do with it
AnalyticsBusiness IntelligencePredictive AnalyticsSocial Data

Social Media Data and what analysts can do with it

3 Min Read
Retail Data Monetization: Are you sitting on top of a retail goldmine?
Big DataBusiness IntelligenceData VisualizationPredictive Analytics

Retail Data Monetization: Are you sitting on top of a retail goldmine?

6 Min Read
The Iceland Volcano Ash – A Great Way to Validate Business Analytics
Business IntelligencePredictive Analytics

The Iceland Volcano Ash – A Great Way to Validate Business Analytics

4 Min Read
The "Avoidability" of Forecast Error [PART 2]
Predictive Analytics

The “Avoidability” of Forecast Error [PART 2]

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
5 Great Tips for Using Data Analytics for Website UX
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?