Book Commentary: Predictive Analytics by Eric Siegel - DoT

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September 22, 2017

Book Commentary: Predictive Analytics by Eric Siegel




As much as we’d like to imagine that today the deployment and use of predictive analysis has now become a commodity for every organization and it’s of use in every “modern” business.

The reality is that in many cases an number of small, medium and even large organizations are still not using predictive analytics and data mining solutions as part of their core software business stack.

Reasons can be plenty: insufficient time, budget or human resources as well as a dose of inexperience and ignorance of its real potential benefits can be the cause. This and other reasons came to my mind when I had the opportunity to read the book: Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die written by former Columbia University professor and founder of Predictive Analytics World conference series, Eric Siegel.

Aside from being a well and clear written book filled with examples and bits of humor to make it enjoyable, what makes this book in my view a one is, mostly written for a general audience, in plain English, which makes it a great option for those new in the field to fully understand what predictive analytics is and the potential effect and benefits for any organization.

With plenty of industry examples and use cases, Mr. Siegel neatly introduces the reader to the world of predictive analytics, what it is, and how this discipline and its tools are currently helping an increasing number organizations in the likes of Facebook, HP, Google, Pfizer ―and other big players in their fields― to discover hidden trends, predict and plan for making better decisions with data.

Another great aspect of the book is also its clear and easy explanation of current important topics including data mining and machine learning as a key to further advanced topics including artificial intelligence and deep learning. It also does a good job of mentioning some caveats and dangers making wrong assumptions when using predictive analytics.

I especially enjoyed the central section of the book filled with examples and use cases predictive analysis in different industries and lines of business like healthcare financial and law enforcement among others as well as list of resources listed at the end of the book.

Of course for me, being a practitioner for many years, there was a small sense of wanting a bit more technical and theoric details but yet, the book is a great introduction reference for both novices that need to get the full potential of predictive analytics and those familiar with the topic but that want to know what their peers are doing to expand their view of the application of predictive analysis in their organization.

If you are still struggling to understand what predictive analysis is and what benefits can offer to your organization can do to improve your decision making and planning abilities, or want a fresh view on what are the new use cases for this discipline and software solutions, Predictive Analytics from Eric Siegel is certainly reference you should consider having in your physical or virtual bookshelf.

Have you read the book? About to do it? Don’t be shy, share your comments right below…

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