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  2. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    The process of dimensional modeling builds on a 4-step design method that helps to ensure the usability of the dimensional model and the use of the data warehouse. The basics in the design build on the actual business process which the data warehouse should cover. Therefore, the first step in the model is to describe the business process which ...

  3. Ralph Kimball - Wikipedia

    en.wikipedia.org/wiki/Ralph_Kimball

    He is one of the original architects of data warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast. [ 2 ] [ 3 ] His bottom-up methodology, also known as dimensional modeling or the Kimball methodology, is one of the two main data warehousing methodologies alongside Bill Inmon .

  4. Enterprise bus matrix - Wikipedia

    en.wikipedia.org/wiki/Enterprise_bus_matrix

    The enterprise bus matrix is a data warehouse planning tool and model created by Ralph Kimball, and is part of the data warehouse bus architecture.The matrix is the logical definition of one of the core concepts of Kimball’s approach to dimensional modeling conformed dimension.

  5. Kimball lifecycle - Wikipedia

    en.wikipedia.org/wiki/Kimball_lifecycle

    The Kimball lifecycle is a methodology for developing data warehouses, and has been developed by Ralph Kimball and a variety of colleagues. The methodology "covers a sequence of high level tasks for the effective design , development and deployment " of a data warehouse or business intelligence system. [ 1 ]

  6. Star schema - Wikipedia

    en.wikipedia.org/wiki/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 .

  7. Degenerate dimension - Wikipedia

    en.wikipedia.org/wiki/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 Ralph Kimball.

  8. Aggregate (data warehouse) - Wikipedia

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

    An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.

  9. 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.