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John W. Foreman [John W. Foreman] - Data Smart: Using Data Science to Transform Information into Insight

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John W. Foreman [John W. Foreman] Data Smart: Using Data Science to Transform Information into Insight

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Data Science gets thrown around in the press like its magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. Its 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 thats done within the familiar environment of a spreadsheet.

Why a spreadsheet? Its 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 dont let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.

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

  • Mathematical optimization, including non-linear programming and genetic algorithms

  • Clustering via k-means, spherical k-means, and graph modularity

  • Data mining in graphs, such as outlier detection

  • Supervised AI through logistic regression, ensemble models, and bag-of-words models

  • Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation

  • Moving from spreadsheets into the R programming language

You 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. Youll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

John W. Foreman [John W. Foreman]: author's other books


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Data Smart Using Data Science to Transform Information into Insight Published - photo 1

Data Smart: Using Data Science to Transform Information into Insight

Published by

John Wiley & Sons, Inc.

10475 Crosspoint Boulevard

Indianapolis, IN 46256

www.wiley.com

Copyright 2014 by John Wiley & Sons, Inc., Indianapolis, Indiana

Published simultaneously in Canada

ISBN: 978-1-118-66146-8

ISBN: 978-1-118-66148-2 (ebk)

ISBN: 978-1-118-83986-7 (ebk)

Manufactured in the United States of America

10 9 8 7 6 5 4 3 2 1

No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 6468600. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions .

Limit of Liability/Disclaimer of Warranty: The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation warranties of fitness for a particular purpose. No warranty may be created or extended by sales or promotional materials. The advice and strategies contained herein may not be suitable for every situation. This work is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional services. If professional assistance is required, the services of a competent professional person should be sought. Neither the publisher nor the author shall be liable for damages arising herefrom. The fact that an organization or Web site is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or website may provide or recommendations it may make. Further, readers should be aware that Internet websites listed in this work may have changed or disappeared between when this work was written and when it is read.

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To my wife, Lydia. What you do each day is impossibly rad. If it weren't for you, I'd have lost my hair (and my mind) eons ago.

Credits

Executive Editor

Carol Long

Senior Project Editor

Kevin Kent

Technical Editors

Greg Jennings

Evan Miller

Production Editor

Christine Mugnolo

Copy Editor

Kezia Endsley

Editorial Manager

Mary Beth Wakefield

Freelancer Editorial Manager

Rosemarie Graham

Associate Director of Marketing

David Mayhew

Marketing Manager

Ashley Zurcher

Business Manager

Amy Knies

Vice President and Executive Group Publisher

Richard Swadley

Associate Publisher

Jim Minatel

Project Coordinator, Cover

Katie Crocker

Proofreader

Nancy Carrasco

Indexer

Johnna van Hoose Dinse

Cover Image

Courtesy of John W. Foreman

Cover Designer

Ryan Sneed

About the Author

John W. Foreman is the Chief Data Scientist for MailChimp.com. He's also a recovering management consultant who's done a lot of analytics work for large businesses (Coca-Cola, Royal Caribbean, Intercontinental Hotels) and the government (DoD, IRS, DHS, FBI). John can often be found speaking about the trials and travails of implementing analytic solutions in businesscheck John-Foreman.com to see if he's headed to your town.

When he's not playing with data, John spends his time hiking, watching copious amounts of television, eating all sorts of terrible food, and raising three smelly boys.

About the Technical Editors

Greg Jennings is a data scientist, software engineer, and co-founder of ApexVis. After completing a master's degree in materials science from the University of Virginia, he began his career with the Analytics group of Booz Allen Hamilton, where he grew a team providing predictive analytics and data visualization solutions for planning and scheduling problems.

After leaving Booz Allen Hamilton, Greg cofounded his first startup, Decision Forge, where he served as CTO and helped develop a web-based data mining platform for a government client. He also worked with a major media organization to develop an educational product that assists teachers in accessing targeted content for their students, and with a McLean-based startup to help develop audience modeling applications to optimize web advertising campaigns.

After leaving Decision Forge, he cofounded his current business ApexVis, focused on helping enterprises get maximum value from their data through custom data visualization and analytical software solutions. He lives in Alexandria, Virginia, with his wife and two daughters.

Evan Miller received his bachelor's degree in physics from Williams College in 2006 and is currently a PhD student in economics at the University of Chicago. His research interests include specification testing and computational methods in econometrics. Evan is also the author of Wizard, a popular Mac program for performing statistical analysis, and blogs about statistics problems and experiment design at http://www.evanmiller.org .

Acknowledgments

T his book started after an improbable number of folks checked out my analytics blog, Analytics Made Skeezy. So I'd like to thank those readers as well as my data science Twitter pals who've been so supportive. And thanks to Aarron Walter, Chris Mills, and Jon Duckett for passing the idea for this book on to Wiley based on my blog's silly premise.

I'd also like to thank the crew at MailChimp for making this happen. Without the supportive and adventurous culture fostered at MailChimp, I'd not have felt confident enough to do something so stupid as to write a technical book while working a job and raising three boys. Specifically, I couldn't have done it without the daily assistance of Neil Bainton and Michelle Riggin-Ransom. Also, I'm indebted to Ron Lewis, Josh Rosenbaum, and Jason Travis for their work on the cover and marketing video for the book.

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