You're reading from Data Exploration and Preparation with BigQuery

Product type Book

Published in Nov 2023

Publisher Packt

ISBN-13 9781805125266

Pages 264 pages

Edition 1st Edition

Languages

Concepts

Data Analysis

Author (1):

Mike Kahn

Table of Contents (21) Chapters

Preface

1. Part 1: Introduction to BigQuery

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

Why subscribe?

20. Other Books You May Enjoy

Analyzing emotions with sentiment analysis

In this section, we will use the ML.UNDERSTAND.TEXT function [2] and a remote model to perform natural language text analysis on our customer support data. Sentiment analysis attempts to determine positive or negative attitudes expressed within text. Sentiment is represented by numerical magnitude and score values. These functions are delivered by BigQuery ML (BQML) and make it possible to analyze text in BigQuery tables, SQL, and Google’s Large Language Models (LLMs).

We will analyze the STRING column instruction in the bitextcustomersupport table to determine the feelings and attitudes of our customers.

Creating a connection

Enable the BigQuery Connection API by searching for this API in the console or visiting https://console.cloud.google.com/marketplace/product/google/bigqueryconnection.googleapis.com and also visit the BigQuery console https://console.cloud.google.com/bigquery. Next, let’s get started with the steps...