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1 Introducing data storytelling

 

This chapter covers

  • What data storytelling is
  • The importance of data storytelling
  • Why you should use Python Altair and generative AI tools for data storytelling
  • When Altair and generative AI tools are not useful for data storytelling
  • How to read this book
  • The data, information, knowledge, wisdom (DIKW) pyramid

By purchasing this book, you have decided to embark on the stimulating path of combining data storytelling, Python, and generative AI. Likely, you already have some knowledge of data visualization and want to learn new techniques to improve your charts and how to use generative AI in the chart creation process. Simply put, by reading this book, you would like to learn how to do data storytelling using generative AI. I’ll tell you right away that the book isn’t only that—it’s more than just background on data storytelling and generative AI. In fact, throughout the book, you will also learn a methodology that will allow you to create your own data-based stories systematically. So it won’t be another book of code and examples to implement, but here and there, I will give you the theoretical basis for implementing your own data-driven stories. This book is a mix of theory and practice, which will allow you to apply the techniques learned in other contexts.

1.1 The art of data storytelling

1.1.1 Why should you use data storytelling?

1.1.2 What problems can data storytelling solve?

1.1.3 What are the challenges of data storytelling?

1.2 Why should you use Python Altair and generative AI for data storytelling?

1.2.1 The benefits of using Python in all the steps of the data science project life cycle

1.2.2 The benefits of using generative AI for data storytelling

1.3 When Altair and generative AI tools are not useful for data storytelling

1.4 Using the data, information, knowledge, wisdom pyramid for data storytelling

1.4.1 From data to information

1.4.2 From information to knowledge

1.4.3 From knowledge to wisdom

Summary

References