Looker Interview Questions: A Comprehensive Guide to Prepare for Your Interview

Are you preparing for an interview at Looker? Looker is a popular business intelligence and data analytics platform that helps organizations make data-driven decisions. As you prepare for your interview, it’s essential to familiarize yourself with the common interview questions that may be asked. In this article, we will provide you with a comprehensive guide to help you prepare for your Looker interview.

Understanding Looker and its Role in Data Analytics

Before diving into the interview questions, it’s crucial to have a clear understanding of Looker and its role in data analytics. Looker is a cloud-based business intelligence platform that allows organizations to explore, analyze, and share data in real-time. It provides a user-friendly interface that enables users to create and customize data visualizations, dashboards, and reports.

Looker is designed to empower organizations by democratizing data access and enabling employees to make data-driven decisions. With Looker, businesses can gain valuable insights into their operations, customer behavior, and overall performance.

15 Common Interview Questions for Looker

1. What is LookML, and how does it work?

LookML is Looker’s modeling language used to define and describe the data relationships in a database. It allows users to create reusable code and build a semantic layer on top of their data. LookML works by translating SQL queries into human-readable code, making it easier for non-technical users to understand and work with data.

2. How do you create a dashboard in Looker?

To create a dashboard in Looker, you start by selecting the relevant data and visualizations you want to include. Then, you can arrange the visualizations on the dashboard and customize their appearance. Looker provides a drag-and-drop interface that simplifies the process of creating and organizing dashboards.

3. Can you explain the concept of dimensions and measures in Looker?

In Looker, dimensions are attributes or fields that provide context to the data. They are typically non-numerical data, such as dates, categories, or names. Measures, on the other hand, are numerical values that can be aggregated or analyzed, such as sums, averages, or counts.

4. How do you optimize performance in Looker?

To optimize performance in Looker, you can use techniques such as caching, indexing, and using appropriate data models. Caching allows Looker to store the results of frequently executed queries, reducing the query execution time. Indexing helps improve query performance by creating indexes on frequently queried columns. Using appropriate data models involves structuring your data in a way that facilitates efficient querying and analysis.

5. How do you schedule and automate reports in Looker?

Looker allows users to schedule and automate reports through its scheduling feature. Users can set the frequency, recipients, and delivery method for the reports. Looker can send reports via email or integrate with third-party tools for automated delivery.

6. How does Looker ensure data security?

Looker prioritizes data security and provides various features to ensure data protection. It offers role-based access control, allowing administrators to define access permissions for users based on their roles and responsibilities. Looker also supports single sign-on (SSO) and integrates with external authentication providers for enhanced security.

7. Can you explain the difference between a filter and a parameter in Looker?

In Looker, a filter is a condition applied to a query to restrict the data returned based on specific criteria. It allows users to dynamically refine their data analysis. On the other hand, a parameter is a user-defined value that can be used to create dynamic queries and calculations. Parameters provide flexibility and allow users to interact with the data in real-time.

8. How do you create a LookML project?

To create a LookML project in Looker, you start by defining a project folder structure and connecting it to your database. Then, you create LookML files that define the data models, explores, and views. Looker’s IDE (Integrated Development Environment) provides a user-friendly interface for writing and organizing LookML code.

9. What are derived tables in Looker?

Derived tables in Looker are tables that are created based on the existing data in the database. They are defined in LookML and can be used to perform complex calculations, transformations, or aggregations on the data. Derived tables provide a way to create customized views of the data without modifying the underlying database.

10. How does Looker handle data governance and data quality?

Looker offers features and best practices to ensure data governance and data quality. It allows administrators to define data access permissions and implement data validation rules. Looker also supports data lineage, which helps track the origin and transformation of data. Additionally, Looker provides data monitoring and alerting capabilities to identify and address data quality issues.

11. How do you create custom visualizations in Looker?

To create custom visualizations in Looker, you can use Looker’s custom visualization API or integrate with third-party visualization tools. Looker’s API allows you to build custom visualizations using JavaScript, HTML, and CSS. You can also leverage Looker’s integration capabilities to embed external visualizations within Looker dashboards.

12. Can you explain Looker’s data modeling best practices?

Looker recommends several best practices for data modeling to ensure efficient and accurate data analysis. Some of these best practices include creating appropriate joins between tables, avoiding unnecessary table scans, using appropriate data types, and partitioning large tables. Following these best practices can significantly improve query performance and data accuracy.

13. How do you handle large datasets in Looker?

When working with large datasets in Looker, it’s essential to optimize query performance and minimize data transfer. You can achieve this by using appropriate data models, applying filters and aggregates, and leveraging Looker’s caching capabilities. Looker also provides options to limit the number of rows returned and paginate through large result sets.

14. How can Looker be integrated with other tools and platforms?

Looker offers various integration options to connect with other tools and platforms. It provides native integrations with popular databases, data warehouses, and data lakes. Looker also supports API integrations, allowing users to automate data workflows and exchange data with external systems. Additionally, Looker can be embedded within other applications using its embedded analytics functionality.

15. How do you handle data security and compliance in Looker?

Looker takes data security and compliance seriously and provides features to meet industry standards. It offers encryption at rest and in transit, ensuring data is protected during storage and transmission. Looker also supports compliance requirements such as GDPR and HIPAA by providing features like data access controls, auditing, and data retention policies.

Preparing for Your Looker Interview

Now that you have an understanding of the common interview questions for Looker, it’s time to prepare for your interview. Here are some tips to help you succeed:

  • Research Looker: Familiarize yourself with Looker’s products, features, and industry presence.
  • Review LookML: Brush up on LookML syntax and best practices to demonstrate your technical knowledge.
  • Practice with Looker: If possible, get hands-on experience with Looker to become familiar with its interface and functionality.
  • Prepare examples: Think about real-life scenarios where you have used data analytics or visualization tools to solve business problems.
  • Highlight your skills: Emphasize your experience with data analytics, SQL, and other relevant technologies.
  • Ask questions: Prepare thoughtful questions to ask the interviewer about Looker’s culture, future plans, and potential growth opportunities.
  • Be confident and enthusiastic: Show your passion for data analytics and your eagerness to contribute to Looker’s mission.

By following these tips and thoroughly preparing for your Looker interview, you’ll increase your chances of success and impress the interviewers with your knowledge and skills.


Preparing for a Looker interview can be challenging, but with the right preparation, you can confidently tackle any question that comes your way. In this article, we covered 15 common interview questions for Looker, along with tips for preparing for your interview. Remember to research Looker, review LookML, and practice with the platform to showcase your expertise. Good luck with your Looker interview!

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