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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [26] Big data requires a set of techniques and technologies with new forms of integration to reveal insights from data-sets that are diverse, complex, and of a massive scale. [27]

  3. Data valuation - Wikipedia

    en.wikipedia.org/wiki/Data_valuation

    Data valuation is a discipline in the fields of accounting and ... have led to a proliferation of big data, ... unused data should be considered to have zero value ...

  4. Master data - Wikipedia

    en.wikipedia.org/wiki/Master_data

    Master data represents "data about the business entities that provide context for business transactions". [1] The most commonly found categories of master data are parties (individuals and organisations, and their roles, such as customers, suppliers, employees), products, financial structures (such as ledgers and cost centres) and locational concepts.

  5. Accounting information system - Wikipedia

    en.wikipedia.org/wiki/Accounting_information_system

    An accounting information system (AIS) is a system of collecting, storing and processing financial and accounting data that are used by decision makers.An accounting information system is generally a computer-based method for tracking accounting activity in conjunction with information technology resources.

  6. Very large database - Wikipedia

    en.wikipedia.org/wiki/Very_large_database

    VLDB is not the same as big data, but the storage aspect of big data may involve a VLDB database. [2] That said some of the storage solutions supporting big data were designed from the start to support large volumes of data, so database administrators may not encounter VLDB issues that older versions of traditional RDBMS's might encounter. [29]

  7. Data - Wikipedia

    en.wikipedia.org/wiki/Data

    In this view, data becomes information by interpretation; e.g., the height of Mount Everest is generally considered "data", a book on Mount Everest geological characteristics may be considered "information", and a climber's guidebook containing practical information on the best way to reach Mount Everest's peak may be considered "knowledge".

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  9. Big data maturity model - Wikipedia

    en.wikipedia.org/wiki/Big_Data_Maturity_Model

    The TDWI big data maturity model is a model in the current big data maturity area and therefore consists of a significant body of knowledge. [6] Maturity stages. The different stages of maturity in the TDWI BDMM can be summarized as follows: Stage 1: Nascent. The nascent stage as a pre–big data environment. During this stage: