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Data Storytelling with Google Looker Studio

You're reading from  Data Storytelling with Google Looker Studio

Product type Book
Published in Oct 2022
Publisher Packt
ISBN-13 9781800568761
Pages 464 pages
Edition 1st Edition
Languages
Author (1):
Sireesha Pulipati Sireesha Pulipati
Profile icon Sireesha Pulipati

Table of Contents (17) Chapters

Preface 1. Part 1 – Data Storytelling Concepts
2. Chapter 1: Introduction to Data Storytelling 3. Chapter 2: Principles of Data Visualization 4. Chapter 3: Visualizing Data Effectively 5. Part 2 – Looker Studio Features and Capabilities
6. Chapter 4: Google Looker Studio Overview 7. Chapter 5: Looker Studio Report Designer 8. Chapter 6: Looker Studio Built-In Charts 9. Chapter 7: Looker Studio Features, Beyond Basics 10. Part 3 – Building Data Stories with Looker Studio
11. Chapter 8: Employee Turnover Analysis 12. Chapter 9: Mortgage Complaints Analysis 13. Chapter 10: Customer Churn Analysis 14. Chapter 11: Monitoring Report Usage 15. Index 16. Other Books You May Enjoy

Building the dashboard- Stage 3: Develop

Now, it’s time to start implementing the dashboard. Creating the data source to power the dashboard is the first step.

Setting up the data source

You need to use Google’s BigQuery connector to create the data source. Since the required data resides in different BigQuery public datasets, using a custom query in the connection settings is the best option. Alternatively, if it’s possible for you, you can create a view (as in, a saved query) or table with the required data fields within BigQuery in your own Google Cloud Project and use this view or table as the dataset to connect to from Looker Studio. The BigQuery sandbox or a GCP free trial will allow you to create tables and views, subject to quotas and other limitations.

Note

The BigQuery public datasets project is read-only and you cannot create tables or views in it.

The custom SQL query to use for defining the data source is as follows:

SELECT
 ...
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