Book Image

Data Smart

By : John W. Foreman
Book Image

Data Smart

By: John W. Foreman

Overview of this book

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. Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, math and the magic, behind big data.
Table of Contents (18 chapters)
Free Chapter
1
Cover
2
Credits
3
About the Author
4
About the Technical Editors
5
Acknowledgments
18
End User License Agreement

But Wait, What about Big Data?

You've heard the term big data even more than data science most likely. Is this a book on big data?

That depends on how you define big data. If you define big data as computing simple summary statistics on unstructured garbage stored in massive, horizontally scalable, NoSQL databases, then no, this is not a book on big data.

If you define big data as turning transactional business data into decisions and insight using cutting-edge analytics (regardless of where that data is stored), then yes, this is a book about big data.

This is not a book that will be covering database technologies, like MongoDB and HBase. This is not a book that will be covering data science coding packages like Mahout, NumPy, various R libraries, and so on. There are other books out there for that stuff.

But that's a good thing. This book ignores the tools, the storage, and the code. Instead, it focuses as much as possible on the techniques. There are many folks out there...