Dimension (data Warehouse)
In a data warehouse, Dimensions provide structured labeling information to otherwise unordered numeric measures. The dimension is a data set composed of individual, non-overlapping data elements. The primary functions of dimensions are threefold: to provide filtering, grouping and labeling.
These functions are often described as "slice and dice". Slicing refers to filtering data. Dicing refers to grouping data. A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product.
A dimensional data element is similar to a categorical variable in statistics.
Typically dimensions in a data warehouse organised internally into one or more hierarchies. "Date" is a common dimension, with several possible hierarchies:
- "Days (are grouped into) Months (which are grouped into) Years",
- "Days (are grouped into) Weeks (which are grouped into) Years"
- "Days (are grouped into) Months (which are grouped into) Quarters (which are grouped into) Years"
- etc.
Read more about Dimension (data Warehouse): Use of ISO Representation Terms, Relationship To Other Components of A Data Warehouse, Common Patterns
Famous quotes containing the word dimension:
“God cannot be seen: he is too bright for sight; nor grasped: he is too pure for touch; nor measured: for he is beyond all sense, infinite, measureless, his dimension known to himself alone.”
—Marcus Minucius Felix (2nd or 3rd cen. A.D.)