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  2. Multi-model database - Wikipedia

    en.wikipedia.org/wiki/Multi-model_database

    In the field of database design, a multi-model database is a database management system designed to support multiple data models against a single, integrated backend. In contrast, most database management systems are organized around a single data model that determines how data can be organized, stored, and manipulated. [1]

  3. Database model - Wikipedia

    en.wikipedia.org/wiki/Database_model

    The inverted file data model can put indexes in a set of files next to existing flat database files, in order to efficiently directly access needed records in these files. Notable for using this data model is the ADABAS DBMS of Software AG, introduced in 1970. ADABAS has gained considerable customer base and exists and supported until today.

  4. System identification - Wikipedia

    en.wikipedia.org/wiki/System_identification

    grey box model: although the peculiarities of what is going on inside the system are not entirely known, a certain model based on both insight into the system and experimental data is constructed. This model does however still have a number of unknown free parameters which can be estimated using system identification.

  5. Entity–relationship model - Wikipedia

    en.wikipedia.org/wiki/Entity–relationship_model

    Consequently, the ER model becomes an abstract data model, [1] that defines a data or information structure that can be implemented in a database, typically a relational database. Entity–relationship modeling was developed for database and design by Peter Chen and published in a 1976 paper, [2] with variants of the idea existing previously. [3]

  6. Zachman Framework - Wikipedia

    en.wikipedia.org/wiki/Zachman_Framework

    The basic model for the focus (or product abstraction) remains constant. The basic model of each column is uniquely defined, yet related across and down the matrix. [26] In addition, the six categories of enterprise architecture components, and the underlying interrogatives that they answer, form the columns of the Zachman Framework and these ...

  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. Identification (information) - Wikipedia

    en.wikipedia.org/wiki/Identification_(information)

    For data storage, identification is the capability to find, retrieve, report, change, or delete specific data without ambiguity. This applies especially to information stored in databases. In database normalisation , the process of organizing the fields and tables of a relational database to minimize redundancy and dependency, is the central ...

  9. Industry standard data model - Wikipedia

    en.wikipedia.org/wiki/Industry_standard_data_model

    An industry standard data model, or simply standard data model, is a data model that is widely used in a particular industry. The use of standard data models makes the exchange of information easier and faster because it allows heterogeneous organizations to share an agreed vocabulary, semantics, format, and quality standard for data.

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