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  2. Data parallelism - Wikipedia

    en.wikipedia.org/wiki/Data_parallelism

    Today, data parallelism is best exemplified in graphics processing units (GPUs), which use both the techniques of operating on multiple data in space and time using a single instruction. Most data parallel hardware supports only a fixed number of parallel levels, often only one.

  3. R (programming language) - Wikipedia

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

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  4. Programming with Big Data in R - Wikipedia

    en.wikipedia.org/wiki/Programming_with_Big_Data_in_R

    Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...

  5. Import and export of data - Wikipedia

    en.wikipedia.org/wiki/Import_and_export_of_data

    The import and export of data is the automated or semi-automated input and output of data sets between different software applications.It involves "translating" from the format used in one application into that used by another, where such translation is accomplished automatically via machine processes, such as transcoding, data transformation, and others.

  6. Data processing - Wikipedia

    en.wikipedia.org/wiki/Data_processing

    Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.

  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

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    By splitting the data into multiple parts, we can check if an analysis (like a fitted model) based on one part of the data generalizes to another part of the data as well. [144] Cross-validation is generally inappropriate, though, if there are correlations within the data, e.g. with panel data . [ 145 ]

  9. Data hierarchy - Wikipedia

    en.wikipedia.org/wiki/Data_hierarchy

    Data field value = Jeffrey Tan The above description is a view of data as understood by a user e.g. a person working in Human Resource Department. The above structure can be seen in the hierarchical model, which is one way to organize data in a database. [2] In terms of data storage, data fields are made of bytes and these in turn are made up ...