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Predictive Analytics, Data Mining and Big Data (Business in the Digital Economy) (Englisch) Gebundene Ausgabe – 29. Juli 2014

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Mehr über den Autor

Steven Finlay is an avid Sci-fi fan and spends a lot of time listening to the music of Mark E Smith and Kraftwerk.

Dr Finlay is also a Data Scientist. He has more than 20 years experience of developing practical "value add" solutions in large scale data environments. He holds a PhD in predictive analytics and is an honorary research fellow at Lancaster University in the UK.

To earn a living, Steve is Head of Analytics at HML, the UKs largest provider of mortgage servicing solutions. Prior to working for HML, he spent several years advising the UK government on the application of predictive analytics, with particular emphasis on overcoming cultural barriers to the use of advanced analytics. Prior to that, he worked for the credit reference agency Experian, managing their UK Analytics Team and leading on the design of Experian's Predictive Analytics software.


Predictive analytics, data mining and big data are key topics for organizations who want to leverage the ever increasing amounts of data that they hold about people. This easy to read, in-depth guide provides readers with a solid understanding of predictive analytics, and how it should be applied to improve business decision making and operational efficiency. This includes how to avoid the pitfalls and dangers of introducing predictive analytics to a business area for the first time, legal, ethical and cultural issues that need to be considered, and a contextual road map for developing solutions that deliver real benefits to organizations. This how-to-guide will help managers to make the most of these technologies in their business area.

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2 von 2 Kunden fanden die folgende Rezension hilfreich
Mapping the interface between predictive analytics and business 12. November 2014
Von Dr Ross Gayler - Veröffentlicht auf
Format: Gebundene Ausgabe
There are plenty of books available on predictive analytics (and data mining and big data - depending on your tolerance for hype), so why should you buy this one? (That's why you are reading this review. Right?)

This book is about predictive analytics as a tool to aid business (in the broadest sense). If that's not your interest this book is not for you. The point is that if predictive analytics is approached as an isolated technical exercise it won't deliver the expected business benefits. In order to be successful the analytics needs to be done with proper recognition of the business context and the business needs to be an informed consumer of analytics. You'd think that would be obvious, but project failures due to a poor interface between the business and the analytics are distressingly common – hence the need for a book like this.

The intended readership appears to be the people on either side of the business/analytics boundary (with a bit of a bias towards the business side). For a reader with an analytics background (but no business experience) the overviews of modelling techniques will probably be superfluous, but the sections on analytics, organisation, culture, ethics, and legislation may be essential eye-openers. On the business side, I would expect the reader to be a middle manager responsible for an analytics-based project or establishing an analytics function (or possibly a business owner who is willing to invest the effort to understand the problem).

There is nothing in this book that is new or revolutionary. It's not that kind of book and that's not the problem it's addressing. Rather, it's more a consciousness-raising check-list. There are a wide range of issues that need to be addressed on the business/analytics interface. This book touches pretty much all of them without giving definitive answers (because the best choice for any specific project is always going to be very context dependent). Consequently, the reader is expected to go off and do other reading in response to the issues raised. The book supports this with extensive appendices, notes, and reading lists.

Steve is well qualified to write this book. He has been a hands-on, pragmatic model builder for many years and has built models for a wider variety of organisations than most. Consequently he has extensive first hand experience of the problems that can arise on the interface between the business and analytics.

In summary, this is not a detailed technical, how-to book. Rather, it is a big picture, “What are we trying to achieve and where does it fit in the organisational context?” book. I would recommend it for anyone who has a hands-on involvement in a business predictive analytics project unless they are an old trouper who has already fallen into every potential trap. The reader must be prepared to do subsequent work, because this book will point out the issues but it's up to the reader to develop the solutions.

(Disclaimer: I know the author. We have been crossing paths at industry conferences for the last 20 years.)
1 von 1 Kunden fanden die folgende Rezension hilfreich
Sound and clear but boring 12. April 2015
Von JohnVidale - Veröffentlicht auf
Format: Kindle Edition Verifizierter Kauf
Focused on business applications. Instructive, but unfortunately that also means repetitive and boring. Frankly, I think the author should have stayed on the data analytics, where he is providing a good primer on the underlying math and the way the analytics often do or don't work. He ventures too often into organizational structure, personnel motivation, and power plays, when his lessons learned did not sound profound or cutting edge.

Still, probably an excellent start to judging when and when not to apply data analytics,
1 von 1 Kunden fanden die folgende Rezension hilfreich
Gem of a Book - Great Intro to Analytics and Data Mining 24. Dezember 2014
Von Alan F. Noel - Veröffentlicht auf
Format: Gebundene Ausgabe
I found this little book to be very informative. Although I have read several other books in this area the past few months none of them have provided so much useful insight into what to do and what to look out for. There are some very good explanations of the basic technology. The book truly dispels some myths and provides practical tips on what the area is about. Yes, there are lots of books around already to drill down into the various technologies but this book is the top of my list for getting a useful introduction.
1 von 1 Kunden fanden die folgende Rezension hilfreich
An excellent book. The book provides not only broad view ... 13. Dezember 2014
Von pansak arpakajorn - Veröffentlicht auf
Format: Gebundene Ausgabe
An excellent book.The book provides not only broad view of big data and predictive analytics, many practical examples and models are also provided with simple explanation.
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