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Data Science for Decision Makers

You're reading from   Data Science for Decision Makers Enhance your leadership skills with data science and AI expertise

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781837637294
Length 270 pages
Edition 1st Edition
Languages
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Author (1):
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Jon Howells Jon Howells
Author Profile Icon Jon Howells
Jon Howells
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Table of Contents (20) Chapters Close

Preface 1. Part 1: Understanding Data Science and Its Foundations
2. Chapter 1: Introducing Data Science FREE CHAPTER 3. Chapter 2: Characterizing and Collecting Data 4. Chapter 3: Exploratory Data Analysis 5. Chapter 4: The Significance of Significance 6. Chapter 5: Understanding Regression 7. Part 2: Machine Learning – Concepts, Applications, and Pitfalls
8. Chapter 6: Introducing Machine Learning 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Unsupervised Machine Learning 11. Chapter 9: Interpreting and Evaluating Machine Learning Models 12. Chapter 10: Common Pitfalls in Machine Learning 13. Part 3: Leading Successful Data Science Projects and Teams
14. Chapter 11: The Structure of a Data Science Project 15. Chapter 12: The Data Science Team 16. Chapter 13: Managing the Data Science Team 17. Chapter 14: Continuing Your Journey as a Data Science Leader 18. Index 19. Other Books You May Enjoy

Empowering and motivating your data science team

Effectively empowering and motivating a data science team requires tapping into their intrinsic drive. As Daniel Pink discusses in his book Drive, the key motivators for knowledge workers are autonomy, mastery, and purpose.

By empowering your data science team by providing autonomy to make decisions, enabling mastery of their field, and connecting their work to a larger purpose, you can tap into the deepest wells of intrinsic motivation. An empowered and motivated team will not only deliver better results but will find fulfillment and meaning in their work, fueling long-term engagement and innovation.

In the next section, we will explore how data science teams engage with other teams and stakeholders and how they can empower other teams to use data. This will further enhance your ability to lead a data-driven organization.

Working with other teams and external stakeholders and empowering them to use data

As a data science...

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