Table of Contents

Part 1: Defining Data Science.- Chapter 1: Understanding Data Science.- Chapter 2: Covering Database Basics.- Chapter 3: Recognizing Different Data Types.- Chapter 4: Applying Statistical Analysis.- Chapter 5: Avoiding Pitfalls in Defining Data Science.- Part 2: Building your Data Science Team.- Chapter 6: Rounding Out Your Talent.- Chapter 7: Forming the Team.- Chapter 8: Starting the Work.- Chapter 9: Thinking Like a Data Science Team.- Chapter 10: Avoiding Pitfalls in Building Your Data Science Team.- Part 3: Delivering in Data Science Sprints.- Chapter 11: A New Way of Working.- Chapter 12: Using a Data Science Lifecycle.- Chapter 13: Working in Sprints.- Chapter 14: Avoiding Pitfalls in Delivering in Data Science Sprints.- Part 4: Asking Great Questions.- Chapter 15: Understanding Critical Thinking.- Chapter 16: Encouraging Questions.- Chapter 17: Places to Look for Questions.- Chapter 18: Avoiding Pitfalls in Asking Great Questions.- Chapter 19: Defining a Story.- Part 5: Storytelling with Data Science.- Chapter 20: Understanding Story Structure.- Chapter 21: Defining Story Details.- Chapter 22: Humanizing Your Story.- Chapter 23: Using Metaphors.- Chapter 24: Avoiding Storytelling Pitfalls.- Part 6: Finishing Up.- Chapter 25: Starting an Organizational Change.- 

About the Author

Doug Rose specializes in organizational coaching, training, and change management. He has worked for over twenty years transforming organizations with technology and training and helping large companies optimize their business processes and improve productivity and delivery. He teaches business and project management courses at the University of Chicago, Syracuse University, and the University of Virginia, and he delivers his online Agile @Work business courses on Lynda.com. He is the author of Leading Agile Teams (PMI Press). Rose has an MS in Information Management and a JD from Syracuse University, and a BA from the University of Wisconsin-Madison.

Reviews

"This fine book ... guides those responsible for building such a team on how to build the best possible data science team for her/his organization. ... It explains not only the internal workings of optimum data science teams, but also the activities that happen around such teams. ... a very useful book for managers who need to create and govern teams that handle data science in the best possible way for their organizations, without having to learn data science." (Computing Reviews, June, 2017)