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  2. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    Design analysis [5] should establish the scalability of an ETL system across the lifetime of its usage – including understanding the volumes of data that must be processed within service level agreements. The time available to extract from source systems may change, which may mean the same amount of data may have to be processed in less time.

  3. Change data capture - Wikipedia

    en.wikipedia.org/wiki/Change_data_capture

    In databases, change data capture (CDC) is a set of software design patterns used to determine and track the data that has changed (the "deltas") so that action can be taken using the changed data. The result is a delta-driven dataset .

  4. Kimball lifecycle - Wikipedia

    en.wikipedia.org/wiki/Kimball_lifecycle

    Physical design is the phase where the database is designed. It involves the database environment as well as security. Extract, transform, load (ETL) design and development is the design of some of the heavy procedures in the data warehouse and business intelligence system.

  5. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    Also, most commercial data analysis tools are used by organizations for extracting, transforming and loading ETL for data warehouses in a manner that ensures no element is left out during the process (Turban et al., 2008). Thus the data analysis tools are used for supporting the 3 Vs in Big Data: volume, variety and velocity. Factor velocity ...

  6. Requirements engineering - Wikipedia

    en.wikipedia.org/wiki/Requirements_engineering

    Requirements analysis and negotiation – Requirements are identified (including new ones if the development is iterative), and conflicts with stakeholders are solved. Both written and graphical tools (the latter commonly used in the design phase, but some find them helpful at this stage, too) are successfully used as aids.

  7. Data collection - Wikipedia

    en.wikipedia.org/wiki/Data_collection

    Data collection and validation consist of four steps when it involves taking a census and seven steps when it involves sampling. [3] A formal data collection process is necessary, as it ensures that the data gathered are both defined and accurate. This way, subsequent decisions based on arguments embodied in the findings are made using valid ...

  8. Value-stream mapping - Wikipedia

    en.wikipedia.org/wiki/Value-stream_mapping

    Value-stream mapping has supporting methods that are often used in lean environments to analyze and design flows at the system level (across multiple processes).. Although value-stream mapping is often associated with manufacturing, it is also used in logistics, supply chain, service related industries, healthcare, [5] [6] software development, [7] [8] product development, [9] project ...

  9. Health systems engineering - Wikipedia

    en.wikipedia.org/wiki/Health_systems_engineering

    Health systems engineering or health engineering (often known as health care systems engineering (HCSE)) is an academic and a pragmatic discipline that approaches the health care industry, and other industries connected with health care delivery, as complex adaptive systems, and identifies and applies engineering design and analysis principles in such areas.

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