Developing Data Models with LookML
This course empowers you to develop scalable, performant Looker ModelingLanguage (LookML) models that provide your business users with the standardized,ready-to-use data that they need to answer their questions. Upon completing thiscourse, you will be able to start building and maintaining LookML models to curateand manage data in your organization’s Looker instance.
- Duration: 1 day
- Languages: English, German
- Level: Intermediate
- Group size: Up to 16
What you'll learn
- Define LookML basic terms and building blocks.
- Model new dimensions and measures using LookML.
- Use dashboards to combine key queries and visualizations into a one-page executive view.
- Model files of LookML projects to design and build custom Explores for business users.
- Use derived tables to create new custom tables that do not exist in the underlying database.
- Explain how caching works and how developers can use datagroups to manage caching policies.
Prerequisites
- To get the most out of this course, participants should have a 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
Course outline
Introducing Looker and LookML
- Looker and LookML
- The Looker user interface
- Example 1: The Looker IDE
- LookML project version control
- Example 2: Git workflow in Looker
- How Looker writes SQL
Data Modeling Using LookML
- Anatomy of a LookML project
- Modeling dimensions
- Example 3: Creating dimensions using LookML
- Modeling measures
- Example 4: Modeling measures using LookML
- Dimension and measure modeling logic
- LookML dashboards
- Lab 1: Creating dimensions and measures with LookML
Modeling Explores for Your Users
- Modeling new Explores
- Using LookML to filter Explores
- Understanding symmetric aggregation
Working with Derived Tables
- Introducing derived tables
- Types of derived tables
- Example 5: Using SQL derived tables
- Example 6: Using native derived tables
- Native derived table parameters
- Using persistent derived tables
- Caching and datagroups
- Implementing datagroups in Looker
- Lab 2: Creating Derived Tables with LookML
Related courses
AlloyDB Essentials
This course explores the benefits of AlloyDB, especially compared to PostgreSQL on Cloud SQL. It will walk you through AlloyDB’s unique architecture, and explain how to configure deployments on Google Cloud.The course is divided into two parts: AlloyDB Administration Essentials (architecture and configuration) and AlloyDB Optimization Essentials (performance tuning).
BigQuery for Data Analysts
This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision-making.
Data Engineering on Google Cloud
Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hands-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data.
Not sure which course fits?
Book a 30-minute call. We'll look at where your team is, what they need to be able to do, and put together either a specific course date or a tailored learning plan.