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Business Intelligence with Looker Cookbook

You're reading from   Business Intelligence with Looker Cookbook Create BI solutions and data applications to explore and share insights in real time

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781800560956
Length 256 pages
Edition 1st Edition
Tools
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Author (1):
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Khrystyna Grynko Khrystyna Grynko
Author Profile Icon Khrystyna Grynko
Khrystyna Grynko
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Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Getting Started with Looker 2. Chapter 2: Configuring Views and Models in a LookML Project FREE CHAPTER 3. Chapter 3: Working with Data in Explores 4. Chapter 4: Customizing and Serving Dashboards 5. Chapter 5: Making Dashboards Interactive through Dynamic Elements 6. Chapter 6: Troubleshooting Looker 7. Chapter 7: Integrating Looker with Other Applications 8. Chapter 8: Organizing the Looker Environment 9. Chapter 9: Administering and Monitoring Looker 10. Chapter 10: Preparing to Develop Looker Applications 11. Index 12. Other Books You May Enjoy

Data tests

Looker provides a couple of tools to ensure the accuracy and integrity of your data models and visualizations:

  • The LookML Validator checks for syntactic errors in your LookML code
  • The Content Validator verifies that object references within your content align with your data model

Data tests (the test parameter) enable you to validate the logic of your model, to perform unit testing before pushing new code into production, by creating queries and corresponding yes/no assertion statements. The data test executes the test query and verifies that the assertion holds true for each row of the query. If the assertion evaluates yes for every row, the data test is considered successful.

The test parameter has the following subparameters:

  • explore_source: Defines the query that provides the data for your test
  • assert: Sets the criteria your data must meet to pass the test

If your project settings mandate that data tests pass before deployment...

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