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  2. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    Example of a star schema; the central table is the fact table. In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation ...

  3. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    Star schema. In computing, the star schema or star model is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. [1] The star schema consists of one or more fact tables referencing any number of dimension tables. The star schema is an important special case of the ...

  4. Slowly changing dimension - Wikipedia

    en.wikipedia.org/wiki/Slowly_changing_dimension

    Slowly changing dimension. A slowly changing dimension ( SCD) in data management and data warehousing is a dimension which contains relatively static data which can change slowly but unpredictably, rather than according to a regular schedule. [1] Some examples of typical slowly changing dimensions are entities such as names of geographical ...

  5. Dimension (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Dimension_(data_warehouse)

    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 labelling. These functions are often described as "slice and dice". A common data warehouse example involves sales as the measure, with customer and product as dimensions.

  6. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    In computing, a snowflake schema or snowflake model is a logical arrangement of tables in a multidimensional database such that the entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. "Snowflaking" is a method of normalizing the ...

  7. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    Dimensions are the foundation of the fact table, and is where the data for the fact table is collected. Typically dimensions are nouns like date, store, inventory etc. These dimensions are where all the data is stored. For example, the date dimension could contain data such as year, month and weekday. Identify the facts

  8. Degenerate dimension - Wikipedia

    en.wikipedia.org/wiki/Degenerate_dimension

    Degenerate dimension. According to Ralph Kimball, [1] in a data warehouse, a degenerate dimension is a dimension key (primary key for a dimension table) in the fact table that does not have its own dimension table, because all the interesting attributes have been placed in analytic dimensions. The term "degenerate dimension" was originated by ...

  9. Dimensional fact model - Wikipedia

    en.wikipedia.org/wiki/Dimensional_fact_model

    Dimensional fact model. The dimensional fact model ( DFM) [1] is an ad hoc and graphical formalism specifically devised to support the conceptual modeling phase in a data warehouse project. DFM can be used by analysts and non-technical users as well. A short-term working is sufficient to realize a clear and exhaustive representation of ...