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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data can include structured, unstructured, or combinations of structured and unstructured data. Big data analysis may integrate raw data from multiple sources. The processing of raw data may also involve transformations of unstructured data to structured data. Other possible characteristics of big data are: [41] Exhaustive

  3. Data-intensive computing - Wikipedia

    en.wikipedia.org/wiki/Data-intensive_computing

    Data-intensive computing is intended to address this need. Parallel processing approaches can be generally classified as either compute-intensive, or data-intensive. [6] [7] [8] Compute-intensive is used to describe application programs that are compute-bound. Such applications devote most of their execution time to computational requirements ...

  4. Datafication - Wikipedia

    en.wikipedia.org/wiki/Datafication

    Data obtained from mobile phones, apps or social media usage is used to identify potential employees and their specific characteristics such as risk taking profile and personality. This data will replace personality tests. Rather using the traditional personality tests or the exams that measure the analytical thinking, using the data obtained ...

  5. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    A cloud-based architecture for enabling big data analytics. Data flows from various sources, such as personal computers, laptops, and smart phones, through cloud services for processing and analysis, finally leading to various big data applications. Cloud computing can offer access to large amounts of computational power and storage. [30]

  6. Primitive data type - Wikipedia

    en.wikipedia.org/wiki/Primitive_data_type

    Integer addition, for example, can be performed as a single machine instruction, and some offer specific instructions to process sequences of characters with a single instruction. [7] But the choice of primitive data type may affect performance, for example it is faster using SIMD operations and data types to operate on an array of floats.

  7. Information retrieval - Wikipedia

    en.wikipedia.org/wiki/Information_retrieval

    Information retrieval is the science [1] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.

  8. Critical data studies - Wikipedia

    en.wikipedia.org/wiki/Critical_data_studies

    First, 'big data' is an important aspect of twenty-first century society, and the analysis of 'big data' allows for a deeper understanding of what is happening and for what reasons. [1] Big data is important to critical data studies because it is the type of data used within this field.

  9. Real-time computing - Wikipedia

    en.wikipedia.org/wiki/Real-time_computing

    The term "near real-time" or "nearly real-time" (NRT), in telecommunications and computing, refers to the time delay introduced, by automated data processing or network transmission, between the occurrence of an event and the use of the processed data, such as for display or feedback and control purposes. For example, a near-real-time display ...