What is fact and dimension in data warehouse?
Facts and dimensions are data warehousing terms. A fact is a quantitative piece of information – such as a sale or a download. Facts are stored in fact tables, and have a foreign key relationship with a number of dimension tables. Dimensions are companions to facts, and describe the objects in a fact table.
What is degenerate and junk dimension?
Degenerate Dimension– A degenerate dimension is when the dimension attribute is stored as part of the fact table and not in a separate table. Junk Dimension– It is a single table with a combination of different and unrelated attributes to avoid having a large number of foreign keys in the fact table.
What are the types of dimensions in data warehouse?
Types of Dimensions are Conformed, Outrigger, Shrunken, Role-playing, Dimension to Dimension Table, Junk, Degenerate, Swappable and Step Dimensions. Five steps of Dimensional modeling are 1.
Why do we need degenerate dimensions?
These degenerate dimensions are natural keys of the “parents” of the line items. Even though there is no corresponding dimension table of attributes, degenerate dimensions can be quite useful for grouping together related fact tables rows.
What is a junk dimension?
A Junk Dimension is a dimension table consisting of attributes that do not belong in the fact table or in any of the existing dimension tables. The nature of these attributes is usually text or various flags, e.g. non-generic comments or just simple yes/no or true/false indicators.
How is a degenerate dimension used in a data warehouse?
Degenerate dimension. According to Ralph Kimball, in a data warehouse, a degenerate dimension is a dimension key in the fact table that does not have its own dimension table, because all the interesting attributes have been placed in analytic dimensions.
Where are degenerate dimensions placed in a fact table?
But the invoice number remains a valid dimension key for fact tables at the line item level. This degenerate dimension is placed in the fact table with the explicit acknowledgment that there is no associated dimension table. Degenerate dimensions are most common with transaction and accumulating snapshot fact tables.
How are junk dimensions used in data warehouse?
Junk dimensions are used to reduce the number of dimensions in the dimensional model and reduce the number of columns in the fact table. A junk dimension combines two or more related low cardinality flags into a single dimension.
What can you do with a degenerate dimension?
You can use the data in the degenerate dimension to limit or ‘slice and dice’ your fact table measures.” This common interpretation implies that it is good dimensional modeling practice to place dimension attributes in the fact table, as long as you call them a degenerate dimension.