Data Science: Create Teams That Ask the Right Questions and Deliver Real Value

by Doug Rose

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

Genres: Technology

276 pages, Paperback

Published November 23, 2016

Reviews

[Dillon Butvin · Rating 4 out of 5]

A good non-technical book on how you should approach data science by asking questions and apply the scientific method to answer those questions.

If you are looking for technical guidance on executing data work, this is NOT the book for you.

If you are looking for guidance on how to take a high-level strategic view to data for business use and how to convey your findings to make lasting change in your organization by reaching people where they are, this is THE book for you. It is very good at that.

The writing was concise, non-fluffed, and enjoyable. I liked it very much.

[Xianshun Chen · Rating 2 out of 5]

the book should be for project manager but i doubt whether it is even good for them considering a lot of points given in the book are not as suitable for at least what i see in our own working environment.

[Willis · Rating 4 out of 5]

As one who is in the middle of this process of building a data science (analytics) team, this was super helpful. This is much less about the tools of data science and much more about how to ask the right questions and the way you should structure the team to be successful. Simple, basic concepts that are so easy to gloss over and forget amidst all the hype around technology and tools. This is crucial to recognize, it is not the tools and technology that will make or break the ability to get the valuable insights from the data. Rather it is the focus to asking the right questions and being able to communicate the insights in the most effective way.