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  2. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g., using data modeling:

  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. YANG - Wikipedia

    en.wikipedia.org/wiki/YANG

    The data modeling language comes with a number of built-in data types. Additional application specific data types can be derived from the built-in data types. More complex reusable data structures can be represented as groupings. YANG data models can use XPATH expressions to define constraints on the elements of a YANG data model.

  5. EXPRESS (data modeling language) - Wikipedia

    en.wikipedia.org/wiki/EXPRESS_(data_modeling...

    An EXPRESS data model can be defined in two ways, textually and graphically. For formal verification and as input for tools such as SDAI the textual representation within an ASCII file is the most important one. The graphical representation on the other hand is often more suitable for human use such as explanation and tutorials.

  6. Generalized additive model for location, scale and shape

    en.wikipedia.org/wiki/Generalized_additive_model...

    For count type response variable data it deals with over-dispersion by using proper over-dispersed discrete distributions. Heterogeneity also is dealt with by modeling the scale or shape parameters using explanatory variables. There are several packages written in R related to GAMLSS models, [3] and tutorials for using and interpreting GAMLSS. [4]

  7. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    AgensGraph is a cutting-edge multi-model graph database designed for modern complex data environments. By supporting both relational and graph data models simultaneously, AgensGraph allows developers to seamlessly integrate legacy relational data with the flexible graph data model within a single database.

  8. Metamodeling - Wikipedia

    en.wikipedia.org/wiki/Metamodeling

    A metamodel is a model of a model, and metamodeling is the process of generating such metamodels. Thus metamodeling or meta-modeling is the analysis, construction, and development of the frames, rules, constraints, models, and theories applicable and useful for modeling a predefined class of problems.

  9. IDEF0 - Wikipedia

    en.wikipedia.org/wiki/IDEF0

    IDEF0 Diagram Example. IDEF0, a compound acronym ("Icam DEFinition for Function Modeling", where ICAM is an acronym for "Integrated Computer Aided Manufacturing"), is a function modeling methodology for describing manufacturing functions, which offers a functional modeling language for the analysis, development, reengineering and integration of information systems, business processes or ...