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The Google LookML-Developer exam covers a range of topics, including LookML modeling, data exploration, advanced LookML, and data modeling best practices. Candidates will be required to demonstrate their ability to write efficient and effective LookML code, as well as their understanding of Looker's data exploration and visualization capabilities. LookML-Developer exam consists of a series of multiple-choice questions and coding challenges, and passing the exam requires a score of at least 70%. Successful candidates will receive a Google LookML-Developer certification, which is a valuable credential for anyone looking to advance their career in data analytics and business intelligence.

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

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The LookML-Developer Certification Exam is designed for individuals who have experience in LookML development and want to prove their mastery of the language. Candidates who pass the exam are recognized as experts in the field of LookML development and are well-equipped to design, create, and maintain Looker data models. LookML-Developer exam consists of multiple-choice questions and requires thorough knowledge of LookML syntax, data modeling concepts, and best practices in Looker development.

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The Google LookML-Developer exam consists of 60 multiple-choice questions and lasts for 90 minutes. It covers a range of topics related to LookML, including data modeling, dimensions and measures, joins, filters, and aggregate functions. It also covers more advanced topics such as derived tables, templated filters, and custom visualizations.

Google LookML-Developer Exam Syllabus Topics:

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

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