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  2. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Data models provide a framework for data to be used within information systems by providing specific definitions and formats. If a data model is used consistently across systems then compatibility of data can be achieved. If the same data structures are used to store and access data then different applications can share data seamlessly.

  3. Data model - Wikipedia

    en.wikipedia.org/wiki/Data_model

    Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.

  4. Semantic data model - Wikipedia

    en.wikipedia.org/wiki/Semantic_data_model

    A semantic data model in software engineering has various meanings: It is a conceptual data model in which semantic information is included. This means that the model describes the meaning of its instances. Such a semantic data model is an abstraction that defines how the stored symbols (the instance data) relate to the real world. [1]

  5. IDEF - Wikipedia

    en.wikipedia.org/wiki/IDEF

    IDEF, initially an abbreviation of ICAM Definition and renamed in 1999 as Integration Definition, is a family of modeling languages in the field of systems and software engineering. They cover a wide range of uses from functional modeling to data, simulation, object-oriented analysis and design, and knowledge acquisition. These definition ...

  6. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    A review and critique of data mining process models in 2009 called the CRISP-DM the "de facto standard for developing data mining and knowledge discovery projects." [ 16 ] Other reviews of CRISP-DM and data mining process models include Kurgan and Musilek's 2006 review, [ 8 ] and Azevedo and Santos' 2008 comparison of CRISP-DM and SEMMA. [ 9 ]

  7. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    Dimensional models are more denormalized and optimized for data querying, while normalized models seek to eliminate data redundancies and are optimized for transaction loading and updating. The predictable framework of a dimensional model allows the database to make strong assumptions about the data which may have a positive impact on performance.

  8. Eclipse Modeling Framework - Wikipedia

    en.wikipedia.org/wiki/Eclipse_Modeling_Framework

    Eclipse Modeling Framework (EMF) is an Eclipse-based modeling framework and code generation facility for building tools and other applications based on a structured data model.

  9. Conceptual schema - Wikipedia

    en.wikipedia.org/wiki/Conceptual_schema

    A data model can be as concrete as each person's perspective, but this tends to make it inflexible. If that person's world changes, the model must change. Conceptual data models take a more abstract perspective, identifying the fundamental things, of which the things an individual deals with are just examples.