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Developing Data Models with LookML
Duration
1
Course
GCP-1708
Available Formats
Classroom Training, Online Training
Course Description
Overview
This Developing Data Models with LookML course is an intermediate-level training that introduces the fundamentals of LookML for Looker developers and provides guided demos and hands-on practice with writing LookML code.Objectives
Upon completion of the Developing Data Models with LookML course, students will be able to:
- Define LookML basic terms and building blocks
- Use the Looker Integrated Development Environment (IDE) and project version control to modify LookML projects
- Create dimensions and measures to curate data attributes used by business users
- Create and design Explores to make data accessible to business users
- Use derived tables to instantaneously create new tables
- Use caching and datagroups in Looker to speed up SQL queries
Audience
Data developers who are responsible for data curation and management within their organizations; Data analysts interested in learning how data developers use LookML to curate and manage data in their organization’s Looker instance.
Prerequisites
- Basic understanding of SQL, Git, and the Looker business user experience.
- For learners with no previous experience as data explorers in Looker, it is recommended to first complete Analyzing and Visualizing Data in Looker.
Topics
The course includes presentations, demonstrations, and hands-on labs.
Module 1: Introduction to Looker and LookML
- Define Looker and the functionality it provides for curating data.
- Define LookML basic terms and building blocks.
- Use the Looker Integrated Development Environment (IDE) to modify LookML projects.
- Create dimensions and measures to curate data attributes used by business users.
- Implement version control with Git to manage and track changes in LookML projects.
- Explain how Looker utilizes SQL on the back end to translate user requests to query results.
- Create and design Explores to make data accessible to business users.
- Use joins to establish relationships between data tables.
- Leverage symmetric aggregation to ensure the accuracy of aggregated metrics.
- Implement filters to preselect data provided to end users.
- Define the two types of derived tables in Looker.
- Create ephemeral and persistent derived tables.
- List best practices for creating derived tables.
- Explain how Looker uses caching to speed up SQL queries.
- Use datagroups to manage caching policies in Looker.
Related Courses
-
Analyzing and Visualizing Data with Looker
GCP-1680- Duration: 1
- Delivery Format: Classroom Training, Online Training
- Price: 595.00 USD
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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title
Please take a moment to fill out this form. We will get back to you as soon as possible.
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