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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. Dimensional fact model - Wikipedia

    en.wikipedia.org/wiki/Dimensional_fact_model

    It can be used from the initial data warehouse life-cycle steps, to rapidly devise a conceptual model to share with customers. Data warehouses (DWs) are databases used by decision makers to analyze the status and the development of an organization. DWs are based on large amounts of data integrated from heterogeneous sources into ...

  4. Data vault modeling - Wikipedia

    en.wikipedia.org/wiki/Data_Vault_Modeling

    Simple data vault model with two hubs (blue), one link (green) and four satellites (yellow) Datavault or data vault modeling is a database modeling method that is designed to provide long-term historical storage of data coming in from multiple operational systems.

  5. Ralph Kimball - Wikipedia

    en.wikipedia.org/wiki/Ralph_Kimball

    Ralph Kimball (born July 18, 1944 [1]) is an author on the subject of data warehousing and business intelligence.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.

  6. Enterprise bus matrix - Wikipedia

    en.wikipedia.org/wiki/Enterprise_bus_matrix

    The bus matrix purpose is one of high abstraction and visionary planning on the data warehouse architectural level. By dictating coherency in the development and implementation of an overall data warehouse the bus architecture approach enables an overall vision of the broader enterprise integration and consistency while at the same time dividing the problem into more manageable parts [2 ...

  7. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  8. Entity–attribute–value model - Wikipedia

    en.wikipedia.org/wiki/Entity–attribute–value...

    An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design. The use-case targets applications which offer a large ...

  9. Common warehouse metamodel - Wikipedia

    en.wikipedia.org/wiki/Common_Warehouse_Metamodel

    The common warehouse metamodel (CWM) defines a specification for modeling metadata for relational, non-relational, multi-dimensional, and most other objects found in a data warehousing environment. The specification is released and owned by the Object Management Group , which also claims a trademark in the use of "CWM".

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