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

Title
Data Science [electronic resource] : Create Teams That Ask the Right Questions and Deliver Real Value / by Doug Rose.
ISBN
9781484222539
Publication
Berkeley, CA : Apress : Imprint: Apress, 2016.
Physical Description
XIX, 251 p. 45 illus., 43 illus. in color : online resource.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
Learn how to build a data science team within your organization rather than hiring from the outside. Teach your team to ask the right questions to gain actionable insights into your business. Most organizations still focus on objectives and deliverables. Instead, a data science team is exploratory. They use the scientific method to ask interesting questions and run small experiments. Your team needs to see if the data illuminate their questions. Then, they have to use critical thinking techniques to justify their insights and reasoning. They should pivot their efforts to keep their insights aligned with business value. Finally, your team needs to deliver these insights as a compelling story. Insight!: How to Build Data Science Teams that Deliver Real Business Value shows that the most important thing you can do now is help your team think about data. Management coach Doug Rose walks you through the process of creating and managing effective data science teams. You will learn how to find the right people inside your organization and equip them with the right mindset. The book has three overarching concepts: You should mine your own company for talent. You can’t change your organization by hiring a few data science superheroes. You should form small, agile-like data teams that focus on delivering valuable insights early and often. You can make real changes to your organization by telling compelling data stories. These stories are the best way to communicate your insights about your customers, challenges, and industry.
Variant and related titles
Springer eBooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
December 01, 2016
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
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Also listed under
SpringerLink (Online service)
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