Google LookML-Developer exam dumps - Looker LookML Developer

  • Exam Code: LookML-Developer
  • Exam Name: Looker LookML Developer
  • Updated: Sep 02, 2026     Q & A: 51 Questions and Answers

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The Looker LookML Developer certification exam covers a range of topics related to LookML, including data modeling, exploring and querying data, designing and creating dashboards, and integrating Looker with other data tools. Successful candidates will be able to demonstrate their ability to design efficient and effective data models, build complex queries, create custom visualizations, and troubleshoot issues with Looker. By earning this certification, developers can showcase their expertise and gain a competitive advantage in the job market.

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The Google LookML-Developer exam is conducted online and consists of 70 multiple-choice questions that must be completed in 90 minutes. LookML-Developer exam is designed to test a candidate's understanding of Looker's data modeling language, LookML, and their ability to use it to build complex data models and visualizations. Candidates are also tested on their proficiency in working with Looker's data exploration and analysis tools, such as dashboards, reports, and advanced analytics.

Reference: https://cloud.google.com/certification/lookml-developer?skip_cache=true

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The Google LookML-Developer exam is offered by Google, which acquired Looker in 2019, and is available to anyone who wants to demonstrate their expertise in LookML. LookML-Developer examination consists of multiple-choice questions and practical tasks that assess the candidate's ability to build and manage LookML models, create custom visualizations, and perform advanced data analysis using Looker.

Google LookML-Developer Exam Syllabus Topics:

SectionObjectives
LookML Fundamentals- Basic LookML syntax
  • 1. Dimensions and measures
    • 2. Derived tables and parameters
      - LookML project structure and components
      • 1. Views, models, and explores
        • 2. Project configuration and files
          Security and Governance- Data governance
          • 1. Field-level security
            • 2. Content validation and consistency
              - Access control
              • 1. User attributes and access filters
                • 2. Permission sets and roles
                  Development Workflow- Testing and validation
                  • 1. Debugging LookML errors
                    • 2. LookML validation tools
                      - Version control
                      • 1. Branching and deployment workflows
                        • 2. Git integration in Looker
                          Data Modeling- Data transformation
                          • 1. Table calculations vs LookML fields
                            • 2. SQL integration in LookML
                              - Relationships and joins
                              • 1. Join types and join logic
                                • 2. Fanouts and symmetric aggregates
                                  Explores and User Experience- Content delivery
                                  • 1. Dashboards and Looks
                                    • 2. Filters and parameters
                                      - Explore design
                                      • 1. Field selection and refinement
                                        • 2. Optimizing explore usability

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