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  2. Critical path method - Wikipedia

    en.wikipedia.org/wiki/Critical_path_method

    The project has two critical paths: activities B and C, or A, D, and F – giving a minimum project time of 7 months with fast tracking. Activity E is sub-critical, and has a float of 1 month. The critical path method ( CPM ), or critical path analysis ( CPA ), is an algorithm for scheduling a set of project activities. [ 1 ]

  3. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  4. Content-oriented workflow models - Wikipedia

    en.wikipedia.org/wiki/Content-oriented_workflow...

    The resource-driven approach demonstrated the application of database triggers for handling workflow events. Still the system implementation is centralized and the workflow schema is statically defined. The project appeared in 2005 but many aspects are considered future work by the authors. Research did not continue on the project.

  5. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    The data modeling process. The figure illustrates the way data models are developed and used today . A conceptual data model is developed based on the data requirements for the application that is being developed, perhaps in the context of an activity model.

  6. Spiral model - Wikipedia

    en.wikipedia.org/wiki/Spiral_model

    The spiral model is a risk-driven software development process model. Based on the unique risk patterns of a given project, the spiral model guides a team to adopt elements of one or more process models, such as incremental , waterfall , or evolutionary prototyping .

  7. Master data management - Wikipedia

    en.wikipedia.org/wiki/Master_data_management

    Master data management (MDM) is a discipline in which business and information technology collaborate to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise's official shared master data assets.

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