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

Apress, 2016. — 247 p. — ISBN: 978-1-4842-2252-2.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.What Your Will Learn
Shows project managers and team leaders how to create data science teams from existing talent in their organizations to cost-efficiently extract maximum business value from their organizations’ data
Introduces managers to key data science terms and concepts
Gives practical guidance on how to create and integrate an effective data science team with key roles and the responsibilities for each team member
Presents the data science life cycle (DSLC) to model essential processes and practices for delivering value
Details the use of sprints and storytelling to help the team stay on track and adapt to new knowledgeThe primary readership for this book is data science project managers and team leaders. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists.Defining Data Science
Understanding Data Science
Covering Database Basics
Recognizing Different Data Types
Applying Statistical Analysis
Avoiding Pitfalls in Defining Data ScienceBuilding Your Data Science Team
Rounding Out Your Talent
Forming the Team
Starting the Work
Thinking Like a Data Science Team
Avoiding Pitfalls in Building Your Data Science TeamDelivering in Data Science Sprints
A New Way of Working
Using a Data Science Life Cycle
Working in Sprints
Avoiding Pitfalls in Delivering in Data Science SprintsAsking Great Questions
Understanding Critical Thinking
Encouraging Questions
Places to Look for Questions
Avoiding Pitfalls in Asking Great QuestionsStorytelling with Data Science
Defining a Story
Understanding Story Structure
Defining Story Details
Humanizing Your Story
Using Metaphors
Avoiding Storytelling PitfallsFinishing Up
Starting an Organizational Change