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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

Best practices for optimizing storage

After preparing and setting up your data, a good area to begin optimizing BigQuery usage is at the storage layer. BigQuery storage is relatively low cost, starting at $0.02 per GB per month (comparable to Cloud Storage or Amazon S3 storage costs) with the first 10 GB of storage per month free. When getting started with BigQuery, the first 10 GB of storage at no cost is a great advantage and creates a frictionless entry point for cost-conscious individuals and businesses. As you begin to load more data, you will want to be aware of the best practices for optimizing storage to operate efficiently and cost-effectively. In this section, we will highlight some of the best practices for managing your data storage in BigQuery.

When you create a dataset, you can set the default table expiration (refer to Figure 10.1). This allows you to set the number of days after creation that the table will be automatically deleted. This is useful for temporary data...

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