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  2. Metadata engine - Wikipedia

    en.wikipedia.org/wiki/Metadata_engine

    Metadata engines virtualize the view of data. Combined with client access protocols such as NFS v4.2 and SMB 2.1 or SMB 3.0 (Samba), a metadata engine can create a global namespace to allow applications to see a logical view of their data, and can orchestrate data movement between different types or tiers of storage without disrupting the application's access to its data.

  3. Metamodeling - Wikipedia

    en.wikipedia.org/wiki/Metamodeling

    For software engineering, several types of models (and their corresponding modeling activities) can be distinguished: Metadata modeling (MetaData model) Meta-process modeling (MetaProcess model) Executable meta-modeling (combining both of the above and much more, as in the general purpose tool Kermeta) Model transformation language (see below)

  4. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]

  5. Data engineering - Wikipedia

    en.wikipedia.org/wiki/Data_engineering

    Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.

  6. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Information technology engineering is a methodology that embraces this approach. 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.

  7. Metadata standard - Wikipedia

    en.wikipedia.org/wiki/Metadata_standard

    Metadata is often defined as data about data. [2] [3] [4] It is “structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use or manage an information resource”, especially in a distributed network environment like for example the internet or an organization. [5]

  8. 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]

  9. Meta-process modeling - Wikipedia

    en.wikipedia.org/wiki/Meta-Process_Modeling

    Meta-process modeling is a type of metamodeling used in software engineering and systems engineering for the analysis and construction of models applicable and useful to some predefined problems. Meta-process modeling supports the effort of creating flexible process models .