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SmartData Collective > Analytics > Data Mining Book Review: Competing on Analytics
Analytics

Data Mining Book Review: Competing on Analytics

SandroSaitta
SandroSaitta
2 Min Read
Data Mining Book Review: Competing on Analytics
Photo by Vijay Richhiya on Pexels (https://www.pexels.com/photo/aerial-view-of-swimming-competition-in-indore-36018788/)
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After reading the excellent book Analytics at Work, I went back in time to read the first book of Davenport and Harris. Competing on Analytics, The New Science of Winning is written for data miners and analytical people as well as for decision makers who are interested in analytics to drive their business. While Analytics at Work concerns any company interested in analytics, Competing on Analytics is written for companies which really focus (compete) on analytics to succeed. Among the most famous are Google, Ebay, Amazon, Netflix, etc.

The book is divided in two parts. The first one explains the analytical competition. The second one shows how to build an analytical-based company. The only issue I had regarding this book is that it is already a little old. For example, genetic algorithms and expert systems are described emerging technologies (!).

In summary, what you will get in this book:

  • Explanation of what analytics is about
  • Stages in which an analytical company can be
  • Several examples of analytics in big companies
  • A guide on how to bring analytics to your company
  • A list of possible application of analytics in a company

What you will not get:

More Read

It's a Bird! It's a Plane! No, It's Just a Data Scientist.
It’s a Bird! It’s a Plane! No, It’s Just a Data Scientist.
Big Data in Big Oil: The Amazing Ways Shell Uses Analytics to Drive Business Success
Extract Meta Concepts Through Co-occurrences Analysis and Graph Theory.
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  • Technical explanations about data mining techniques
  • Equations or algorithms

This book is a must-have guide for any person serious about applying analytics to a company. It’s a well written story of possible applications of analytics. After reading this book, I would advise Analytics at Work which really explains concrete methods to bring all these notions to work.

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