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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

Understanding query structure

A BigQuery query is an SQL statement that is used to select, filter, and transform data stored in BigQuery tables. To effectively query data in BigQuery, it is essential to understand the structure of a query and the purpose of each element. A BigQuery query follows a specific syntax and consists of various clauses that work together to retrieve the desired information from your datasets. Let’s break down the sections of a SQL query in BigQuery in detail.

Action command – the SELECT clause

The commands that are used in the SELECT area of your query tell the analysis engine what needs to be done. SELECT extracts data from a table.

The SELECT clause chooses the columns you want to retrieve in the result. It determines what data you want from a table and defines calculations or transformations. You can specify columns to be returned by name or use the wildcard operator (*) to select all columns (note that it is not advised to use this...

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