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Database Design and Modeling with Google Cloud

You're reading from   Database Design and Modeling with Google Cloud Learn database design and development to take your data to applications, analytics, and AI

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781804611456
Length 234 pages
Edition 1st Edition
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Author (1):
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Abirami Sukumaran Abirami Sukumaran
Author Profile Icon Abirami Sukumaran
Abirami Sukumaran
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Database Model: Business and Technical Design Considerations
2. Chapter 1: Data, Databases, and Design FREE CHAPTER 3. Chapter 2: Handling Data on the Cloud 4. Part 2:Structured Data
5. Chapter 3: Database Modeling for Structured Data 6. Chapter 4: Setting Up a Fully Managed RDBMS 7. Chapter 5: Designing an Analytical Data Warehouse 8. Part 3:Semi-Structured, Unstructured Data, and NoSQL Design
9. Chapter 6: Designing for Semi-Structured Data 10. Chapter 7: Unstructured Data Management 11. Part 4:DevOps and Databases
12. Chapter 8: DevOps and Databases 13. Part 5:Data to AI
14. Chapter 9: Data to AI – Modeling Your Databases for Analytics and ML 15. Chapter 10: Looking Ahead – Designing for LLM Applications 16. Index 17. Other Books You May Enjoy

Unstructured data analytics with BigQuery

In this section, we will put the theory of storing unstructured data in BigQuery and querying it into action. If you are wondering why we are storing unstructured data in BigQuery, refer to the Storage options in BigQuery section:

  1. Go to Cloud Storage from the Google Cloud console and select the bucket we created previously (bucket-demo-gc).
  2. Click Upload Files under the Objects section and select your files.
  3. Once the upload is complete, you should be able to see the files in the bucket, as shown here:
Figure 7.10: The Cloud Storage Bucket page with its objects listed

Figure 7.10: The Cloud Storage Bucket page with its objects listed

  1. Head over to the BigQuery console by searching for it in the Google Cloud console and enable the APIs as required (it is pretty self-explanatory with the console prompts).
  2. Create a dataset by clicking the three dots next to your project name and click Create data set.
  3. Provide your Data set ID, Location type, and other...
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