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Our Data Science e-Book provides recipes, intriguing discussions and resources for data scientists and executives or decision makers. You don't need an advanced degree to understand the concepts. Most of the material is written in simple English, however it offers simple, better and patentable solutions to many modern business problems, especially about how to leverage big data.

Emphasis is on providing high-level information that executives can easily understand, while being detailed enough so that data scientists can easily implement our proposed solutions. Unlike most other data science books, we do not favor any specific analytic method nor any particular programming language: we stay one level above practical implementations. But we do provide recommendations about which methods to use when necessary.

Most of the material is original, and  can be used to develop better systems, derive patents or write scientific articles. We also provide several rules of the thumbs and details about craftsmanship used to avoid traditional pitfalls when working with data sets. The book also contains interviews with analytic leaders, and material about what should be included in a business analytics curriculum, or about how to efficiently optimize a search to fill an analytic position.

Among the more technical contributions, you will find notes on

  • How to determine the number of clusters
  • How to implement a system to detect plagiarism
  • How to build an ad relevancy algorithm
  • What is a data dictionary, and how to use it
  • Tutorial on how to design successful stock trading strategies
  • New fast, safe and efficient random number generator
  • How to detect patterns vs. randomness

The book has three parts:

  • Part I: Data science recipes
  • Part II: Data science discussions
  • Part III: Data science resources

Part I and II mostly consist of the best Analyticbridge posts by Dr. Vincent Granville, founder of Analyticbridge. Part III consists of sponsored vendor contributions as well contributions by organizations (affiliates offering software, conferences, training, books, etc.) who make our free e-book available for download on their web site. To become a sponsor or affiliate, please contact us at [email protected]

To read updates about our book and download a draft version (to be published by December), visit

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Would Analytic Science be a better title than Data Science?
I like "Data Science" more than "Analytic Science"; however based on your synopsis of the book it seeks like "Analytic Science" might be more appropriate.  For marketing purposes I would try something a little more flashy like "Datonometrics - Explorations in applied analytics and data."  Take if for what it's worth - I'm a grad student :)
It definitely fits with the Analytic Bridge branding.  Yet to me both are appropriate.

Very excited to see this!!  I'd love to read a draft when it's available!!


I like "Analytic Science" - I think it will encompass a broader audience for sales - for you and it sounds more intriguing from a marketing perspective.  I'm thinking back to how well "Competing on Analytics" sold and still does.  People tend to make those associations in their head.  It will, of course, not change your content, just to whom the book may appeal - a broader audience for sales.  Congrats!


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