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  2. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [ 1 ]

  3. List of data-erasing software - Wikipedia

    en.wikipedia.org/wiki/List_of_data-erasing_software

    Printable version; In other projects Wikidata item; Appearance. move to sidebar hide. This is a list of utilities for ... List of data-erasing software.

  4. Data editing - Wikipedia

    en.wikipedia.org/wiki/Data_editing

    Data editing is defined as the process involving the review and adjustment of collected survey data. [1] Data editing helps define guidelines that will reduce potential bias and ensure consistent estimates leading to a clear analysis of the data set by correct inconsistent data using the methods later in this article. [2]

  5. List of spreadsheet software - Wikipedia

    en.wikipedia.org/wiki/List_of_spreadsheet_software

    Sourcetable [9] – AI spreadsheet that generates formulas, charts, SQL, and analyzes data. ThinkFree Online Calc – as part of the ThinkFree Office online office suite, using Java; Quadratic - A source available online spreadsheet for technical users, supporting Python, SQL, and Formulas.

  6. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...

  7. Data reduction - Wikipedia

    en.wikipedia.org/wiki/Data_reduction

    Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications

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