UK Oracle User Group


Book Review - Predictive Analytics Using Oracle Data Miner

Book Review - Predictive Analytics Using Oracle Data Miner

16 September 2014

"Makes a complex subject easy to learn - a perfect way to get into Data Mining and Predictive BI." Antony Heljula, UKOUG member

Each year McGraw Hill offer our members free books in return for an honest review of the content.

One of the books available to our members for review this year was Predictive Analytics Using Oracle Data Miner: Develop for ODM in SQL & PL/SQL by Brendan Tierney. 

Read our members' reviews of this book below to decide whether or not it will be worth your investment in this title.

 

 

Antony Heljula of Peak Indicators gave this book a rating of 5 out of 5 stars

I found this book to be the perfect way to learn Oracle Data Mining or Predictive Analytics. For years I have known that data-mining existed but never really knew what it did behind the scenes or how it worked. After reading this book for only a brief period I had gained enough knowledge to talk to customers about the concepts, capabilities and benefits of data mining and start suggesting ideas on how Predictive Analytics would give them real business value.

The nice thing is that the author has made an effort to keep things at a high-level - there is no need to talk in depth about how complex data mining algorithms work - all the low-levels details about data mining algorithms can easily be found on Google should you wish to know!

What the author does well is focus on is the types of algorithms available and why you would want to use each one. This is then backed up with working examples (which you can also repeat) of how to perform each type of algorithm (the author provides examples for both Oracle Data Miner front-end user interface and PL/SQL).

The book also talks about the end-to-end process for a data mining project, and also includes installation/setup instructions.

One question I have heard many times is "how do you know when your predictive model is accurate enough"? All these types of questions are answered in the book.

We have members of staff who are wanting to get into data mining - this book will be recommended to them.

 

To read more member reviews of Oracle titles, please go here

If you're a member and would like to contribute book reviews, keep your eye on this page for review opportunities. Thanks to McGraw-Hill for this opportunity and to Antony for taking the time to review the book's contents. We hope you find his insights helpful.

We'd love to get your feedback on this; you'll need a UKOUG login to provide it, so if you don't have one, please click on 'create a web profile' first.

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