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Data Exploration and Preparation with BigQuery

You're reading from  Data Exploration and Preparation with BigQuery

Product type Book
Published in Nov 2023
Publisher Packt
ISBN-13 9781805125266
Pages 264 pages
Edition 1st Edition
Languages
Author (1):
Mike Kahn Mike Kahn
Profile icon Mike Kahn
Toc

Table of Contents (21) Chapters close

Preface 1. Part 1: Introduction to BigQuery
2. Chapter 1: Introducing BigQuery and Its Components 3. Chapter 2: BigQuery Organization and Design 4. Part 2: Data Exploration with BigQuery
5. Chapter 3: Exploring Data in BigQuery 6. Chapter 4: Loading and Transforming Data 7. Chapter 5: Querying BigQuery Data 8. Chapter 6: Exploring Data with Notebooks 9. Chapter 7: Further Exploring and Visualizing Data 10. Part 3: Data Preparation with BigQuery
11. Chapter 8: An Overview of Data Preparation Tools 12. Chapter 9: Cleansing and Transforming Data 13. Chapter 10: Best Practices for Data Preparation, Optimization, and Cost Control 14. Part 4: Hands-On and Conclusion
15. Chapter 11: Hands-On Exercise – Analyzing Advertising Data 16. Chapter 12: Hands-On Exercise – Analyzing Transportation Data 17. Chapter 13: Hands-On Exercise – Analyzing Customer Support Data 18. Chapter 14: Summary and Future Directions 19. Index 20. Other Books You May Enjoy

Technical requirements

The dataset we use in this exercise is the Historic Vehicle GPS Data: Department of Public Services (2016) dataset. This hands-on example is intended to replicate a real-life scenario based on vehicle location data and a transportation data use case.

You may wish to use your existing Google Cloud project for this exercise or create a new one. If you wish to use a new project, do the following:

  1. Within the Cloud console, click the project selector on the top menu bar to open the project selection dialog box.
  2. From within the project selection window, you can create a new project for this exercise.

Figure 12.1 – The project selection dialog box

To follow along with this chapter you will need to bring the following data source into your BigQuery project. We will review step by step how to load the dataset into BigQuery later in this chapter. For now, you can download each file locally to your computer so it will...

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