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  2. DICE framework - Wikipedia

    en.wikipedia.org/wiki/DICE_framework

    The DICE framework, or Duration, Integrity, Commitment, and Effort framework is a tool for evaluating projects, [1] predicting project outcomes, and allocating resources strategically to maximize delivery of a program or portfolio of initiatives, aiming for consistency in evaluating projects with subjective inputs.

  3. Open Source Tripwire - Wikipedia

    en.wikipedia.org/wiki/Open_Source_Tripwire

    Open Source Tripwire is a free software security and data integrity tool for monitoring and alerting on specific file change(s) on a range of systems [2] [3] originally developed by Eugene H. Spafford and Gene Kim. [4] The project is based on code originally contributed by Tripwire, Inc. in 2000.

  4. Data integrity - Wikipedia

    en.wikipedia.org/wiki/Data_integrity

    An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...

  5. Precisely (company) - Wikipedia

    en.wikipedia.org/wiki/Precisely_(company)

    Precisely Holdings, LLC, doing business as Precisely, is a software company specializing in data integrity tools, and also providing big data, high-speed sorting, ETL, data integration, data quality, data enrichment, and location intelligence offerings.

  6. 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.

  7. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").

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