Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 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
SHARE

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.

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 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.

More Read

R for psychological research
House Hearing on Hedge Funds
Recently, spectacular advances in medical imaging combined with…
From Decision Support Systems to Decision Management Systems
Lyza – Supporting Collaborative Process in Decision Making

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.

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

AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic
data intelligence in healthcare
How Data Is Powering Real-Time Intelligence in Health Systems
Big Data Exclusive
intersection of data
The Intersection of Data and Empathy in Modern Support Careers
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

big data analytics
AnalyticsExclusiveMarketingNewsPredictive Analytics

How to Use Analytics for Effective Content Marketing

6 Min Read

What’s Wrong with Today’s Planning and Budgeting

8 Min Read

Mobile Advertising, Clustering Algorithms, and Your Ticket for a Free Ride

5 Min Read

IBM Podcast: Retailers Respond to Economic and Consumer…

0 Min Read

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

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?