Google-LookML-Developer - Study Material - Google LookML Developer

The Google LookML Developer exam is an exam designed to assess a candidate's knowledge and ability to develop LookML models for Google BigQuery using the Looker platform. The exam covers topics such as creating and managing LookML models, working with Looker's visualizations and data exploration tools, and understanding the Looker platform's architecture.

There is no set duration for the Google LookML Developer Exam. The exam is designed to assess the candidate's knowledge and skills in developing LookML models, and the amount of time it takes to complete the exam will vary depending on the individual's experience and familiarity with the material.

There is no set number of questions for the Google Google-LookML Developer Exam. The exam consists of a mixture of multiple-choice, true/false and open-ended questions designed to test the applicant's knowledge of LookML and its related technologies.

Google does not provide an exact passing score for the Google LookML Developer exam. However, applicants should aim to score at least 70% in order to pass.

The Competency Level required for Google Google-LookML-Developer exam is Google Cloud Certified - Professional Data Engineer.

The Google Google-LookML Developer exam consists of multiple choice and multiple select questions.

The Google Google-LookML Developer exam can be taken either online or in a testing center. Online exams are administered via the Google Cloud Platform, and testing centers are located around the world. To take the exam online, you must have access to a computer with an internet connection and a webcam. To take the exam in a testing center, you must register for the exam and provide valid identification.

Google does not offer a Google-LookML-Developer Exam.

The cost of the Google Google-LookML Developer Exam is $150.

The target audience of the Google Google-LookML Developer Exam is software engineers who have hands-on experience developing LookML applications. It is also suitable for developers who have a good understanding of the LookML language, its concepts and tools, and who want to demonstrate their expertise in this area.

The average salary for a Google-LookML Developer varies depending on experience and location. According to Glassdoor, the national average salary for a Google-LookML Developer is $108,000. However, salaries can range from $70,000 to $150,000 depending on experience and location.

Google does not offer an official Google-LookML-Developer exam. However, there are third-party providers that offer practice tests and other resources to help you prepare for the exam.

The recommended experience for the Google Google-LookML-Developer exam is a minimum of one year of experience in developing LookML models. This experience should include the ability to create, debug, and optimize LookML models, as well as the ability to work with data sources, explore data, and use LookML functions. Additionally, the candidate should have experience with SQL, data modeling, and data warehousing concepts.

The Google LookML Developer Certification Exam does not have any prerequisites. However, it is recommended that you have at least one year of professional experience working with LookML and/or a related technology like SQL, Python, or R, and a basic understanding of the LookML syntax and structure.

The official website to check the expected retirement date of the Google LookML Developer exam is: https://cloud.google.com/certification/guides/lookml-developer/retirement-dates

1. Complete the Google LookML Developer Fundamentals course. 2. Become familiar with the LookML language and tooling. 3. Take the Google LookML Developer Practice Exam. 4. Take and pass the Google LookML Developer Certification Exam.

1. Introduction to LookML: This topic covers the fundamentals of LookML, including its purpose, structure, and syntax. It also covers the basics of data modeling and how LookML can be used to create data models. 2. LookML Syntax and Semantics: This topic covers the syntax and semantics of LookML, including how to write valid LookML code. It also covers the advanced features of LookML, such as parameters, views, and transformations. 3. LookML Development Workflows: This topic covers the development workflows for creating LookML projects, including how to create, test, and deploy LookML projects. 4. LookML Best Practices: This topic covers best practices for creating LookML projects, including how to optimize performance, troubleshoot errors, and debug LookML code. 5. LookML Deployment and Maintenance: This topic covers the deployment and maintenance of LookML projects, including how to deploy LookML

1. What is LookML and how is it used to create data models? 2. How do you create a new project in LookML? 3. Describe the process of creating and managing views in LookML. 4. What are the different types of data transformation available in LookML? 5. Explain the process of creating and managing dashboards in LookML. 6. What are the different types of visualizations available in LookML? 7. Describe the process of creating and managing access controls in LookML. 8. How do you debug and troubleshoot LookML code? 9. Describe the process of creating and managing data sources in LookML. 10. What are the best practices for writing efficient LookML code?

The Google Google-LookML-Developer exam has an intermediate difficulty level.