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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

Data loading from CSV upload

In the previous two chapters, we loaded data from a local file and from Google Cloud Storage. For this example, we will load data again using local CSV files. If you have not already, download the two datasets in the Technical requirements section to your local workstation so you can load them into BigQuery.

Follow these steps to load our example datasets into BigQuery:

  1. Open the BigQuery console: https://console.cloud.google.com/bigquery.
  2. Select your project and create a new dataset:

Figure 13.3 – Create a new dataset in an expanded project in the BigQuery console

  1. Give the dataset the dataset ID ch13, keep it set to multi-region US, and leave all options as the default. Click Create dataset.
  2. Click the three dots on your newly created dataset and click Create table, as shown in the following screenshot.

Figure 13.4 – Create a table in the newly created...

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