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  2. 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.

  3. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Data modeling during systems analysis: In systems analysis logical data models are created as part of the development of new databases. Data modeling is also used as a technique for detailing business requirements for specific databases. It is sometimes called database modeling because a data model is eventually implemented in a database. [4]

  4. Modeling and simulation - Wikipedia

    en.wikipedia.org/wiki/Modeling_and_simulation

    Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making. [1] [2]

  5. Semantic spectrum - Wikipedia

    en.wikipedia.org/wiki/Semantic_spectrum

    Taxonomy: A complete data model in an inheritance hierarchy where all data elements inherit their behaviors from a single "super data element". The difference between a data model and a formal taxonomy is the arrangement of data elements into a formal tree structure where each element in the tree is a formally defined concept with associated ...

  6. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  7. Ontology (information science) - Wikipedia

    en.wikipedia.org/wiki/Ontology_(information_science)

    Improved ontologies may improve problem solving within that domain, interoperability of data systems, and discoverability of data. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. [ 2 ]

  8. Taxonomy - Wikipedia

    en.wikipedia.org/wiki/Taxonomy

    Human Factors Analysis and Classification System, a system to identify the human causes of an accident; Swiss cheese model, a model used in risk analysis and risk management propounded by Dante Orlandella and James T. Reason; A taxonomy of rail incidents in Confidential Incident Reporting & Analysis System (CIRAS)

  9. Category:Data modeling - Wikipedia

    en.wikipedia.org/wiki/Category:Data_modeling

    In information system design, data modeling is the analysis and design of the information in the system, concentrating on the logical entities and the logical dependencies between these entities Contents