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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

Identifying data ethical concerns

When it comes to ethical concerns about data, we see that this topic has grown in prominence in recent years. This is because, in our digital big data era, we create masses more data every day, as discussed in previous chapters. But this data, whether pertaining to an individual or a business, can often be personal or sensitive, and open to exploitation by cybercriminals or others looking to exploit or use this information for negative gain.

Initially, this was a kind of gray area as there were no particular rules defined. People just did amazing things, such as predicting when a website visitor booked an airplane ticket online that they also would buy insurance (a sort of classification was used here). Wherever we could lay our hands on data from an internal and external perspective, we could do amazing things without even worrying about rules or ethical concerns.

But today, the data ethics landscape is different. Issues such as the ownership...

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