Becoming a Data Head. Alex J. Gutman

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 website 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.

      For general information on our other products and services please contact our Customer Care Department within the United States at [phone], outside the United States at [phone] or fax [phone].

      Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com.

      Library of Congress Control Number: 2021934226

      Trademarks: Wiley and the Wiley logo are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates, in the United States and other countries, and may not be used without written permission. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc. is not associated with any product or vendor mentioned in this book.

      ISBN: 978-1-119-74174-9

      ISBN: 978-1-119-74176-3 (ebk)

      ISBN: 978-1-119-74171-8 (ebk)

      For my children Allie, William, and Ellen.

      Allie was three when she discovered dad was a “doctor.” Puzzled, she looked at me and said, “But, you don't help people… .” In that spirit, I also dedicate this book to you, the reader.

      I hope this helps you. —Alex

       For Stephen and Melissa —Jordan

About the Authors

      Alex J. Gutman is a data scientist, corporate trainer, Fulbright Specialist grant recipient, and Accredited Professional Statistician® who enjoys teaching a wide variety of data science topics to technical and non-technical audiences. He earned his Ph.D. in applied math from the Air Force Institute of Technology where he currently serves as an adjunct professor.

      Jordan Goldmeier is an internationally recognized analytics professional and data visualization expert, author, and speaker. A former chief operations officer at Excel.TV, he has spent years in the data training trenches. He is the author of Advanced Excel Essentials and Dashboards for Excel. His work has been cited by and quoted in the Associated Press, Bloomberg BusinessWeek, and American Express OPEN Forum. He is currently an Excel MVP Award holder, an achievement he's held for six years, allowing him to provide feedback and direction to Microsoft product teams. He once used Excel to save the Air Force $60 million. He is also a volunteer Emergency Medical Technician.

About the Technical Editors

      William A. Brenneman is a Research Fellow and the Global Statistics Discipline Leader at Procter & Gamble in the Data and Modeling Sciences Department and an Adjunct Professor of Practice at Georgia Tech in the Stewart School of Industrial and Systems Engineering. Since joining P&G, he has worked on a wide range of projects that deal with statistics applications in his areas of expertise: design and analysis of experiments, robust parameter design, reliability engineering, statistical process control, computer experiments, machine learning, and statistical thinking. He was also instrumental in the development of an in-house statistics curriculum. He received a Ph.D. in Statistics from the University of Michigan, an MS in Mathematics from the University of Iowa, and a BA in Mathematics and Secondary Education from Tabor College. William is a Fellow in both the American Statistical Association (ASA) and the American Society for Quality (ASQ). He has served as ASQ Statistics Division Chair, ASA Quality and Productivity Section Chair, and as Associate Editor for Technometrics. William also has seven years of experience as an educator at the high school and college level.

      Jennifer Stirrup is the Founder and CEO of Data Relish, a UK-based AI and Business Intelligence leadership boutique consultancy delivering data strategy and business-focused solutions. Jen is a recognized leading authority in AI and Business Intelligence Leadership, a Fortune 100 global speaker, and has been named as one of the Top 50 Global Data Visionaries, one of the Top Data Scientists to follow on Twitter, and one of the most influential Top 50 Women in Technology worldwide.

      Jen has clients in 24 countries on 5 continents, and she holds postgraduate degrees in AI and Cognitive Science. Jen has authored books on data and artificial intelligence and has been featured on CBS Interactive and the BBC as well as other well-known podcasts, such as Digital Disrupted, Run As Radio, and her own Make Your Data Work webinar series.

      Jen has also given keynotes for colleges and universities, as well as donated her expertise to charities and non-profits as a Non-Executive Director. All of Jen's keynotes are based on her 20+ years of global experience, dedication, and hard work.

Acknowledgments

      I've noticed a trend in acknowledgment sections—the author's spouse is often mentioned at the end. I suppose it's a saving-the-best-for-last gesture, but I promised my wife if I ever wrote a book, I'd mention her first to make it perfectly clear whose contributions mattered most to me. So, to my wife Erin, thank you for your love, encouragement, and smile. As I write this, you are taking our three young children on a bike ride, giving me time to write one final page. (I assure all readers this act is a representative sample of our lives this past year.)

      I'd also like to thank my parents, Ed and Nancy, for being the best cheerleaders in whatever I do and for showing me what being a good parent looks like, and to my siblings Ryan, Ross, and Erin for their support.

      This book is the culmination of many discussions with friends and colleagues, ranging from whether I should attempt to write a book about data literacy to potential topics that should appear in it. Thank you especially to Altynbek Ismailov, Andy Neumeier, Bradley Boehmke, Brandon Greenwell, Brent Russell, Cade Saie, Caleb Goodreau, Carl Parson, Daniel Uppenkamp, Douglas Clarke, Greg Anderson, Jason Freels, Joel Chaney, Joseph Keller, Justin Maurer, Nathan Swigart, Phil Hartke, Samuel Reed, Shawn Schneider, Stephen Ferro, and Zachary Allen.

      I'm also indebted to the hundreds of engineers, business professionals, and data scientists I've interacted with, personally or online, who've taught me how to be a better data scientist and communicator. And to my “students” (colleagues) who have given candid feedback about the courses I've taught, I heard you and I thank you.

      I'm fortunate to have many academic and professional mentors who've given me numerous opportunities to find my voice and confidence as a statistician, data scientist, and trainer. Thank you to Jeffery Weir, John Tudorovic, K. T. Arasu, Raymond Hill, Rob Baker, Scott Crawford, Stephen Chambal, Tony White, and William Brenneman (who kindly served as a technical editor on this book). It's impossible not to become wiser hanging around a group like that.

Thanks to the team at Wiley: Jim Minatel for believing in the project and giving us a chance, Pete Gaughan and John Sleeva for guiding us through the process, and the production staff at Wiley for meticulously combing through our chapters. And to our technical