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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

Concepts

Author (1):

Mike Kahn

Table of Contents (21) Chapters

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

Why subscribe?

20. Other Books You May Enjoy

Summary

This chapter went through the power and versatility of using Jupyter notebooks for data exploration. We went over the different notebook options available for usage in Google Cloud including Vertex AI Workbench instances and Colab notebooks. Each service has a specific target user and both are collaborative and have the same general purpose – extending your BigQuery data exploration with Python and JupyterLab. With practical examples and step-by-step instructions, the chapter equips you with the necessary knowledge to effectively explore and prepare data, using notebooks in conjunction with BigQuery.

In the next chapter, we will delve into exploring and visualizing data to enable you further, with even more options to explore data in BigQuery. Take a look at the links in the Further reading section for additional information related to this chapter.

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Authors (1)

Mike Kahn

Mike Kahn is a data and infrastructure enthusiast and currently leads a Customer Engineering team at Google Cloud. Prior to Google, Mike spent five years in solution architecture roles and worked in operations and leadership roles in the data center industry. His over 15 years of experience have given him a deep knowledge of data and infrastructure engineering, operations, strategy, and leadership. Mike holds multiple Google Cloud certifications and is a lifelong learner. He is based in Boca Raton, Florida, in the US and holds a Bachelor of Science degree in Management Information Systems (MIS) from University of Central Florida and a Master of Science degree in MIS from Florida International University.

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