Which of the following is a true statement about dimension fields in Looker?

Which of the following is a true statement about dimension fields in Looker?

• A. They can only use aggregate functions
• B. They can be used to filter data
• C. They do not contribute to measures
• D. They are only numeric fields

Answer: (B)

Dimension fields in Looker are used primarily to describe data and can indeed be utilized for filtering. They often represent qualitative attributes such as names, categories, or dates, which allow users to segment or refine the data analysis. When creating queries in Looker, dimensions enable users to specify the criteria for the data they want to include in their results, making them critical for generating meaningful insights. In contrast, the other choices do not accurately represent the capabilities of dimension fields. Dimension fields can perform various functions beyond filtering, including being part of the data's context when measures are aggregated. They may also consist of non-numeric values, such as strings or categorical data, further emphasizing their role in data representation rather than restriction to numeric types. Thus, stating that they can be used to filter data highlights one of their fundamental and versatile features.

Dimension fields in Looker are used primarily to describe data and can indeed be utilized for filtering. They often represent qualitative attributes such as names, categories, or dates, which allow users to segment or refine the data analysis. When creating queries in Looker, dimensions enable users to specify the criteria for the data they want to include in their results, making them critical for generating meaningful insights.

In contrast, the other choices do not accurately represent the capabilities of dimension fields. Dimension fields can perform various functions beyond filtering, including being part of the data's context when measures are aggregated. They may also consist of non-numeric values, such as strings or categorical data, further emphasizing their role in data representation rather than restriction to numeric types. Thus, stating that they can be used to filter data highlights one of their fundamental and versatile features.