# Learn the analytical techniques, the math and the magic behind big data, be data smart.

## Review of Data Smart

The following is a review of the book Data Smart: Using Data Science to Transform Information into Insight** **by John Foreman, Chief Product Officer at MailChimp and professional Data Scientist.

Data Science and Machine Learning are belief to be magic by many, some sort of whimsical field for mathematicians and geniuses. However, this is far from being true. Data Science can be easy, if you know how to do it right, and almost anyone can do it.

The goal of Data Smart is to show that anybody that is willing to learn a few concepts can do Data Science, even with no programming or complex software knowledge. How? you might ask. The answer is simple and controversial at the same time: using the worldwide known and familiar environment of a spreadsheet.

Yes, you’ve heard it. In this book, the author solves problems like genetic algorithms, K-means, Supervised Machine Learning algorithms, Natural Language processing, and Time Series using excel.

While it is clear that this is not the best available tool (Foreman is aware of it, and explains that R or Python are probably better for these kind of tasks), the goal here is to show you the most significant data science techniques, how they work, how to use them, and how they benefit your business, large or smal**l**. It’s not about coding or database technologies. It’s about turning raw data into insight you can act upon, and doing it as quickly and painlessly as possible.

The goal of the book is to teach its readers to do Data Science in the right way: understanding the true problem that has to be solved, avoiding focusing on things that don’t matter, and the fact that, as a data scientist, you are not the most important part of a business — you are there to help make the most important parts better.

Don’t get fooled by the use of excel tough, the techniques covered in the book are complex, and if you are looking for a basic intro to Data Analysis you should probably avoid this text and go for something easier like Python for Data Analysis, that will also teach you some programming.

**In data smart you will learn the analytic techniques, the math and the magic, behind big data, explained by an expert in the field in a humorous and easy to follow manner.** It is a very practical book, with which you will get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You’ll even learn what a dead squirrel has to do with optimisation modeling, which you no doubt are dying to know.

The contents of the book cover:

- Artificial intelligence using the general linear model, ensemble methods, and naive Bayes
- Clustering via k-means, spherical k-means, and graph modularity
- Mathematical optimisation, including non-linear programming and genetic algorithms
- Working with time series data and forecasting with exponential smoothing
- Using Monte Carlo simulation to quantify and address risk
- Detecting outliers in single or multiple dimensions
- Exploring the data-science-focused R language

## About the Book

**Author: **John Foreman, Chief Product Officer at Mailchimp and professional Data Scientist. A great communicator that makes complex topics as simple as tying our shoe lazes.

**Length**: 432 pages.

**Book’s official website.** In here you will find the data and spreadsheet templates used in the Book, along with further information.

## Summary of Data Smart

Data Smart is a wonderful book for understanding the complexity of Data Science and how to best use it for your advantage. Data Science is about analysing data, making predictions and getting insights, and should not be considered as a goal but rather as a tool to improve our overall quality of life.

This book is about proper data science material that has genuine applicability in the real world. It is not for the very beginners, however if you have some experience and can get your head around the contents of this book you’ll be well-placed to add real value in any organisation.

Data Smart is a very hands-on and guide that gives you a tool set you can actually use and constitutes a text that is very valuable and well worth the effort.

- Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.
- But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.
- Foreman, John W. (Author)
- English (Publication Language)
- 432 Pages - 11/12/2013 (Publication Date) - Wiley (Publisher)

For more books like this one, take a look at our Data Analysis section. Thank you so much for reading How to learn Machine Learning, and have a fantastic day!

## Quotes about the book

“*Data Smart makes modern statistic methods and algorithms understandable and easy to implement. Slogging through textbooks and academic papers is no longer required*!” **Patrick Crosby**, Founder of StatHat & first CTO at OkCupid

“*When Mr. Foreman interviewed for a job at my company, he arrived dressed in a ‘Kentucky Colonel’ kind of suit and spoke about nonsensical things like barbecue, lasers, and orange juice pulp. Then, he explained how to de-mystify and solve just about any complex ‘big data’ problem in our company with simple spreadsheets. No server clusters, mainframes, or Hadoop-a-ma-jigs. Just Excel. I hired him on the spot. After reading this book, you too will learn how to use math and basic spreadsheet formulas to improve your business or, at the very least, how to trick senior executives into hiring you as their data scientist.*“** Ben Chestnut**, Founder & CEO of MailChimp

“*You need a John Foreman on your analytics team. But if you can’t have John, then reading this book is the next best thing*.”** Patrick Lennon**, Director of Analytics, The Coca-Cola Company