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
About the Author
About the Technical Editors
End User License Agreement

Why Should Data Scientists Know Optimization?

If you watch a bunch of James Bond or Mission Impossible movies, you'll notice that they often have a big action sequence before the opening credits. Nothing draws viewers in like an explosion.

The previous chapters on data mining and artificial intelligence were just that—our explosions. But now, like in any good action movie, the plot must advance. In Chapter 2 you used a bit of optimization modeling in finding the optimal placement of cluster centroids, but you had only been given enough optimization knowledge in Chapter 1 to make that happen. In this chapter, you're going to dive deep into optimization and get lots of experience with how to formulate models that solve business problems.

Artificial intelligence is making waves these days for its use at tech companies and start-ups. Optimization, on the other hand, seems to be more of a Fortune 500 business practice. Reengineering your supply chain to reduce the fuel costs...