What type of results does content validation provide in Looker?

• A. Error-free models
• B. Content that uses non-existent or untraceable names
• C. Performance metrics on queries
• D. Recommendations for optimization

Answer: (B)

Content validation in Looker is primarily designed to identify issues related to the integrity and accuracy of your LookML code. When performing content validation, Looker checks for dependencies and references within your models, ensuring that all elements, such as measures, dimensions, and views, are properly defined and linked.

In this context, the results provided by content validation specifically point out any content that uses non-existent or untraceable names. This means that if there is a reference to a field or object that does not exist in the model or is incorrectly spelled, content validation will flag this as an issue. It helps developers catch these errors early, preventing potential runtime errors or misleading reports when users query the data.

The focus on identifying undefined references is critical for maintaining a clean and functional LookML model, which is essential for delivering accurate analytics. Thus, the emphasis of content validation aligns with ensuring all names used within the LookML are valid and correctly spelled, rather than providing guarantees of overall model functionality, performance metrics, or optimization recommendations.