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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

Product type Paperback

Published in Nov 2022

Publisher Packt

ISBN-13 9781803246758

Length 396 pages

Edition 1st Edition

Concepts

Data Analysis

Authors (2):

Kevin Hanegan

Angelika Klidas

View More author details

Table of Contents (21) Chapters

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

Why subscribe?

20. Other Books You May Enjoy

Managing Data and Analytics Projects

In this chapter, we’ll talk about how data and analytics projects are different from other types of projects, why it’s important to take care of typical data and analytics risks, and why it’s a good idea to find out who your stakeholders are. Then, we’ll talk about how to write a good (short, strong) data and analytics business case.

By the end of this chapter, you’ll understand how data and analytics projects work, how to identify and manage stakeholders, and how to handle common data and analytics risks. We will also advise and guide you through the process of writing your data and analytics business case and conducting a complete financial analysis.

In this chapter, we will cover the following topics:

Discovering why data and analytics projects fail
Understanding four typical data and analytics project characteristics
Understanding data and analytics project blockers
Unfolding the data...

The rest of the chapter is locked

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Authors (2)

Angelika Klidas

Angelika Klidas

Angelika is a highly skilled denizen of the Data world. As operations manager for several organizations, strategic advisor and Data Literacy evangelist, she is able to analyze BI & Analytics environments expertly, map the ambitions of organizations and deliver cutting-edge advice to help organizations mature their data use. Inspiring organizations and people to grow in Business Intelligence & Analytics maturity is her passion. In addition to teaching at the University of Applied Sciences in Amsterdam, where she spreads her knowledge and passion to her Data & Analytics students

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Kevin Hanegan

Kevin Hanegan

Kevin has helped individuals and organizations maximize the value they receive from their data for over 20 years. He is a is a frequent speaker and thought leader on topics including data literacy, data-informed decision making, decision intelligence, and essential skills for today's workforce. He is currently the Chief Learning Officer at Qlik, a data and analytics company, as well as the chair of the advisory board for The Data Literacy Project. Kevin is also an accomplished author of multiple books, including Turning Data into Wisdom, which helps individuals learn strategies to make data-informed decisions. He applies his passion both in the corporate setting and also in academia where he is an adjust professor at Boise State University.

See other products by Kevin Hanegan

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