Book Review: R for Business Analytics, A Ohri

October 26, 2012
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(This article was first published on Intelligent Trading, and kindly contributed to R-bloggers)


      I've added a recently released book to my list of recommendations (at the amazon carousel to the right), as I've reviewed a copy provided to me via Springer Publishers. The book is R for Business Analytics, authored by A Ohri.  Mr. Ohri provides us with a brief background of his own journey as a business analytics consultant, and shares how R helped complement his work with a very low cost (time to learn the software) and very large benefits.  At the outset, he emphasizes that the book is not geared towards statisticians, but more towards practicing business analytics professionals, MBA students, and pragmatically oriented R neophytes and professionals alike. In addition, there is a focus on using GUI oriented tools towards assisting users in quickly getting up to speed and applying business analysis tools (Rattle, for example, is covered as an alternative to Weka, which has been covered here previously).  In addition, he provides numerous interviews with well known company representatives who have either successfully integrated R into their own development flow (including JMP/SAS, Google, and Oracle ), or found that large groups of customers have utilized R to augment their existing suite of tools.  The good news is that many of the large companies do not view R as a threat, but as a beneficial tool to assist their own software capabilities.

     After assisting and helping R users navigate through the dense forest of various GUI interface choices (in order to get R up and running), Mr. Ohri continues to handhold users through step by step approaches (with detailed screen captures) to run R from various simple to more advanced platforms (e.g. CLOUD, EC2) in order to gather, explore, and process data, with detailed illustrations on how to use R's powerful graphing capabilities on the back-end.

     The book has something for both beginning R users (who may be experienced in data science, but want to start learning how to apply R towards their field), and experienced R users alike (many, like myself, may find it useful to have a very broad coverage of the myriad number of packages and applications available, complemented by quickly accessible tutorial based illustrations).  In summary, the book has an extremely broad coverage of R's many packages that can be used towards business data analysis, with a very hands on approach that can help many new users quickly come up to speed and running on utilizing R's powerful capabilities-- on the down-side, it is short on depth and mathematical rigour (leaving the door open to pursue several more specialized R texts).

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