Cover image for Data smart : using data science to transform information into insight
Title:
Data smart : using data science to transform information into insight
Author:
Foreman, John W., author.
Personal Author:
Publication Information:
Hoboken, New Jersey : John Wiley & Sons, [2014]

©2014
Physical Description:
xx, 409 pages : illustrations ; 24 cm
Summary:
"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."--
General Note:
Companion website.

Includes index.
Language:
English
Contents:
Everything you ever needed to know about spreadsheets but were too afraid to ask -- Cluster analysis part I : using K-means to segment your customer base -- Naïve Bayes and the incredible lightness of being an idiot -- Optimization modeling : because that "fresh squeezed" orange juice ain't gonna blend itself -- Cluster analysis part II : network graphs and community detection -- The granddaddy of supervised artificial intelligence : regression -- Ensemble models : a whole lot of bad pizza -- Forecasting : breathe easy; you can't win -- Outlier detection : just because they're odd doesn't mean they're unimportant -- Moving from spreadsheets into R -- Conclusion.
ISBN:
9781118661468
Format :
Book

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Summary

Summary

Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions.

But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope.

Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart , author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet.

Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype.

But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data.

Each chapter will cover a different technique in aspreadsheet so you can follow along:

Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language

You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.


Author Notes

John W. Foreman is Chief Data Scientist for MailChimp.com, where he leads a data science product development effort called the Email Genome Project. As an analytics consultant, John has created data science solutions for The Coca-Cola Company, Royal Caribbean International, Intercontinental Hotels Group, Dell, the Department of Defense, the IRS, and the FBI.