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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. Industrial big data - Wikipedia

    en.wikipedia.org/wiki/Industrial_Big_Data

    Industrial big data refers to a large amount of diversified time series generated at a high speed by industrial equipment, [1] known as the Internet of things. [2] The term emerged in 2012 along with the concept of "Industry 4.0”, and refers to big data”, popular in information technology marketing, in that data created by industrial equipment might hold more potential business value. [3]

  4. 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 ...

  5. Data as a service - Wikipedia

    en.wikipedia.org/wiki/Data_as_a_service

    In this business model, data provides value as a support mechanism or a tool for creating other value propositions, that's why the revenue stream is typically quite a bit lower. [19] In turn, Data as a Service is one of 3 categories of big data business models based on their value propositions and customers: Answers as a Service;

  6. 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:

  7. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:

  8. The 3 best stock market and Wall Street movies that every ...

    www.aol.com/finance/3-best-stock-market-wall...

    If you don’t know some of the terms used to describe the causes of the housing bubble, don’t worry. The movie uses celebrities to explain concepts and terms, like mortgage-backed securities .

  9. 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. [40]