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Data Exploration and Preparation with BigQuery

You're reading from   Data Exploration and Preparation with BigQuery A practical guide to cleaning, transforming, and analyzing data for business insights

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781805125266
Length 264 pages
Edition 1st Edition
Languages
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Author (1):
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Mike Kahn Mike Kahn
Author Profile Icon Mike Kahn
Mike Kahn
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Introduction to BigQuery FREE CHAPTER
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

Using Workbench notebook instances in Vertex AI

This section provides an overview of the notebooks available in Google Cloud and their significance in relation to data exploration and preparation in BigQuery. Workbench notebooks are a powerful component of the Vertex AI platform, enabling data analysts and data scientists to perform data exploration within a collaborative and unified environment. Workbench notebooks are a JupyterLab VM-based offering that can be configured for specific usage scenarios. Let’s discuss this data exploration tool in more detail.

Workbench notebooks provide a unified interface, where data analysts and scientists can work seamlessly on projects. Multiple team members can collaborate on the same notebook, making it easy to share insights, exchange ideas, and work toward data goals. Vertex AI Workbench (https://cloud.google.com/vertex-ai-workbench) offers two types of notebook options, managed notebooks with built-in integrations, and user-managed...

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