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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

Layout information and measure plan

Elements that should be written down in an information measure plan are as follows:

  1. An introduction:
    1. A short description of your information measure plan
    2. A problem analysis
    3. The objectives of your project
    4. The scope (what are you going to do and what not)
  2. The information necessity for management:
    1. Describe the KPIs and reports that are needed
    2. Who your users are (have a look at Figure 7.16, Chapter 7)
    3. Describe the desired level of granularity (the level of detail)
    4. Describe the nonfunctional requirements (see the intake form that we added here in the template chapter)
  3. User stories/use cases/requirements:
    1. User story 1
    2. User story 2
    3. And so on
  4. Data sources:
    1. Desired sources
    2. Data quality check
    3. Describe the missing data
    4. Describe the metadata
  5. The solution:
    1. Describe the dashboard and reports (follow the DARs principle – see Chapter 7)
    2. Describe and sketch the data flow
    3. Design the dashboard (using the chatting and sketching technique that is described...
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