What do 'dimensions' in data sources typically represent?

Dimensions in data sources typically represent qualitative attributes or categories of data. They provide context to quantitative data and help in organizing and slicing the data for analysis. For example, if you have sales data, dimensions could include attributes such as product categories, geographical locations, or customer demographics. These dimensions allow users to analyze data across various categories and derive insights into specific segments of the dataset.

While quantitative measurements of data involve numerical values and can be analyzed mathematically, dimensions serve as the categorical frameworks that help explain and interpret these quantitative aspects. Time-based data records may also relate to dimensions in certain contexts (like analyzing sales over different time periods) but do not comprehensively represent what dimensions are. Database metadata refers to data about other data, which is different from the concept of dimensions that focuses on attributes for analysis.