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Data Literacy in Practice

You're reading from   Data Literacy in Practice A complete guide to data literacy and making smarter decisions with data through intelligent actions

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781803246758
Length 396 pages
Edition 1st Edition
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Authors (2):
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Kevin Hanegan Kevin Hanegan
Author Profile Icon Kevin Hanegan
Kevin Hanegan
Angelika Klidas Angelika Klidas
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Angelika Klidas
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Understanding the Data Literacy Concepts
2. Chapter 1: The Beginning – The Flow of Data FREE CHAPTER 3. Chapter 2: Unfolding Your Data Journey 4. Chapter 3: Understanding the Four-Pillar Model 5. Chapter 4: Implementing Organizational Data Literacy 6. Chapter 5: Managing Your Data Environment 7. Part 2: Understanding How to Measure the Why, What, and How
8. Chapter 6: Aligning with Organizational Goals 9. Chapter 7: Designing Dashboards and Reports 10. Chapter 8: Questioning the Data 11. Chapter 9: Handling Data Responsibly 12. Part 3: Understanding the Change and How to Assess Activities
13. Chapter 10: Turning Insights into Decisions 14. Chapter 11: Defining a Data Literacy Competency Framework 15. Chapter 12: Assessing Your Data Literacy Maturity 16. Chapter 13: Managing Data and Analytics Projects 17. Chapter 14: Appendix A – Templates 18. Chapter 15: Appendix B – References 19. Index 20. Other Books You May Enjoy

Creating a data literacy educational program

In the previous section, we talked about the importance of managing skills and competencies. One key element of this framework is the ability to upskill your employees on these skills and competencies. The specific skills and competencies are discussed later on in Chapter 11, Defining a Data Literacy Competency Framework, but for now, it is important to know that these are a combination of hard skills and soft skills. When most organizations invest in data literacy education and data literacy maturity models, they tend to focus on hard skills. They often talk about capabilities in terms of technology and tools, but they often leave out the necessary soft skills to become fully data literate.

An organization may build many dashboards and reports, but then just hope that the business can use them appropriately. Other times, organizations will put data literacy training in place for their employees, but they make it one size to fit all....

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