In the context of database schemas, what is a Dimension Table?

A Dimension Table is essential in the realm of data warehousing and online analytical processing (OLAP). It is designed to hold descriptive attributes, also known as dimensions, which provide context to the metrics stored within a fact table. These attributes are typically textual and allow users to slice and dice data for reporting purposes.

For example, in a sales database, a dimension table could include details about products (like name, category, and brand), time (like day, week, or month), or geography (like city, state, or country). This descriptive context helps users understand the "who, what, where, when, and why" behind the metrics they are analyzing, such as total sales or revenue figures.

In contrast, a table that contains measures only would refer to a fact table, which focuses on quantitative data rather than the qualitative descriptions. A table that holds normalized data may be more relevant in the context of operational databases rather than data warehousing. Lastly, a table responsible for indexing data is not related to the core functions of a dimension table; indexing is a method used to improve the performance of queries rather than to provide descriptive context. Thus, the choice indicating that a Dimension Table contains the descriptive context for metrics accurately captures its fundamental role