Data Science Book Review: Data Smart
If you want to get started with Data Science and don’t like learning a new language such as R or Python, then this book is a perfect fit for you. Entertaining, Data Smart: Using Data Science to Transform Information into Insight approaches data science from a unusual angle. John W. Foreman has written a book for those who wants to apply data mining without using advanced programming (R, Python, etc.). It doesn’t mean you don’t need to understand what data science is, and this book is very good at explaining it to non-practitioners.
Foreman’s book is written in a nice and funny stile, which makes it an easy read. Data mining algorithms are described with the minimum equations needed. Foreman has written a practical book and thus decided to use Excel as a tool for data science. The book starts with an introduction to Excel and its most famous functions. For data scientists using SAS, R, Python or Matlab, you may discover how powerful Excel is. But you will also see how clumsy it is to use Excel for data science. Whereas you would need a few lines in R, the book will take you through a dozen pages of step by step actions you need to perform to obtain the same in Excel. Not only is it more time consuming but also more prone to errors.
Don’t get me wrong: Data Smart is excellent at explaining how to perform data science in Excel. I just think Excel is not the right tool for it. The book is also a journey into MailChimp, the author’s company. This is nice and provides plenty of examples related to e-mail marketing. The book thus provides quick and high-level description of the problem, followed by Excel steps to solve it. In conclusion, Data Smart is a must read to get a fresh perspective on data science with a “Data Science using Excel” user manual. And for the experts? You can just skip the Excel parts and get insights into the field, with a focus on MailChimp use cases.