gegevensdimensies

Gegevensdimensies, often translated as data dimensions, are the attributes or characteristics used to categorize and segment data. In data analysis and business intelligence, dimensions provide context and allow for a deeper understanding of the underlying information. They are typically qualitative or descriptive, as opposed to measures, which are quantitative and represent the actual values being analyzed.

Common examples of data dimensions include time (e.g., year, month, day), geography (e.g., country, region, city), product (e.g., category, brand, item), and customer (e.g., demographics, segment). By pivoting or slicing data along these dimensions, users can explore trends, identify patterns, and answer specific business questions. For instance, analyzing sales data by product dimension might reveal which products are performing best, while analyzing it by time dimension could show seasonal sales fluctuations.

In a dimensional modeling context, dimensions are stored in separate tables, often referred to as dimension tables, which are linked to fact tables. Fact tables contain the quantitative measures and foreign keys referencing the dimension tables. This structure is fundamental to the design of data warehouses and data marts, enabling efficient querying and reporting. The richness and granularity of dimensions directly impact the analytical capabilities and the insights that can be derived from the data.