Data Mining Book Review: Analytics in a Big Data World

9781118892701.pdfI just finished reading the new book of Bart Baesens: Analytics in a Big Data World, the essential guide to data science and its applications. Before starting this review, let’s be clear from the very beginning: this book is not about Big Data. It neither discusses the philosophy behind Big Data, nor the technical architecture supporting it. The misleading title is the only weak point of this excellent book.

Bart has succeeded to summarize key analytics algorithms and concepts in a few sentences. Each concept is very well explained with both plain text and equations. Although very frequent, they are well explained and help understand algorithms. The book introduction is a journey into how business analytics is used nowadays. Topics such as data preparation, predictive/descriptive analytics and social network analytics are covered.

I would like to highlight the excellent backtesting digital dashboards (p. 145) with lots of practical advices. The last chapter of the book covers applications such as fraud detection, churn prediction and recommender systems among others. In conclusion, if you’re not afraid of equations and would like to get the best coverage of business analytics algorithms, this book is perfect for you!

Analytics in a Big Data World: The Essential Guide to Data Science and its Applications (Wiley and SAS Business Series)


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  1. I work on the implicative interestingness of association rule independently denoted as ION by Totohasina A., CPIR by X. WU, MGK by Guillaume. I defined a normalised quality measure of association rule under five conditions.

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