Looker is a data platform that helps developers and businesses explore, visualize, and understand their data. It turns large amounts of raw data into useful charts, dashboards, and reports that people can use to make better decisions. LookML is the special language used inside Looker to define how data is organized and connected, so it’s easier to work with.
For developers, learning Looker and LookML means they can create custom data experiences for users—like interactive dashboards or tailored reports—without needing to rewrite code every time. It allows teams to share insights across departments and make sure everyone is working with the same accurate information. It’s a powerful way to turn complex data into something clear and useful.
Who should take the Exam?
This exam is ideal for:
Data analysts
BI developers
Data engineers
SQL developers
Professionals working in data governance or analytics
Technical project managers
Teams transitioning to modern BI platforms
Cloud engineers involved in GCP/BigQuery-based analytics
Skills Required
Intermediate SQL proficiency
Familiarity with data warehousing concepts
Understanding of dimensions, metrics, joins
Basic experience with data visualization tools
Analytical thinking and structured problem-solving
Knowledge Gained
Fundamentals of Looker platform and architecture
Building and organizing LookML projects
Defining and managing dimensions, measures, and views
Creating Explores and refining data access
Implementing version control and development workflows
Enforcing performance and security best practices
Building user-friendly dashboards and reports
Integrating Looker with external tools or APIs
Course Outline
The Looker and LookML for Developers Exam covers the following topics -
1. Introduction to Looker and LookML
What is Looker?
Benefits of using LookML
Overview of Looker architecture
2. Understanding LookML Syntax and Structure
Files: model, view, explore
LookML syntax rules
Modularity and reusability
3. Building LookML Views
Declaring dimensions and measures
Types of fields (string, number, date)
SQL parameters in LookML
Derived tables and persistent derived tables (PDTs)
4. Creating Models and Explores
Model files: basics and configuration
Defining Explores and joins
Control access with access_filter
Using always_filter, sets, and substitutions
5. Looker Development Environment
Looker IDE and Git integration
Version control workflows
Working with branches and pull requests
6. Data Governance and Performance Tuning
Optimizing LookML queries
Avoiding N+1 problems
Managing user permissions
Using persist_with and datagroup
7. Dashboard Design and Visualization
Creating Looks and dashboards
Filters, tiles, and visual options
Best practices in UX design for data
8. Advanced Features in Looker
Liquid templating in LookML
Custom visualizations
Looker Actions and webhooks
Embedding and API integration
What We Offer?
Full-Length Mock Tests that include unique, exam-style questions to help you practice under real conditions.
Section-Wise Practice Questions for reviewing topic-based questions and instantly see where you stand in every section.
Detailed answers with a clear and thorough explanation to help you understand the concept, not just memorize answers.
Get a complete breakdown of your strengths, weaknesses, and progress after every attempt.
All question sets reflect the latest exam syllabus and format.
Unlimited Access to Practice anytime, as often as you want - no time limits or hidden restrictions.
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