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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data analytics has been used in healthcare in providing personalized medicine and prescriptive analytics, clinical risk intervention and predictive analytics, waste and care variability reduction, automated external and internal reporting of patient data, standardized medical terms and patient registries.

  3. 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:

  4. Big data ethics - Wikipedia

    en.wikipedia.org/wiki/Big_data_ethics

    Big data ethics, also known simply as data ethics, refers to systemizing, defending, and recommending concepts of right and wrong conduct in relation to data, in particular personal data. [1] Since the dawn of the Internet the sheer quantity and quality of data has dramatically increased and is continuing to do so exponentially.

  5. 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:

  6. Continuous analytics - Wikipedia

    en.wikipedia.org/wiki/Continuous_analytics

    Analytics is the application of mathematics and statistics to big data. Data scientists write analytics programs to look for solutions to business problems, like forecasting demand or setting an optimal price. The continuous approach runs multiple stateless engines which concurrently enrich, aggregate, infer and act on the data.

  7. Social data analysis - Wikipedia

    en.wikipedia.org/wiki/Social_data_analysis

    Social data analysis can provide a new slant on business intelligence where social exploration of data can lead to important insights that the user of analytics did not envisage/explore. The term was introduced by Martin Wattenberg in 2005 [2] and recently also addressed as big social data analysis in relation to big data computing.

  8. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    KNIME: The Konstanz Information Miner, a user-friendly and comprehensive data analytics framework. Massive Online Analysis (MOA): a real-time big data stream mining with concept drift tool in the Java programming language. MEPX: cross-platform tool for regression and classification problems based on a Genetic Programming variant.

  9. Prescriptive analytics - Wikipedia

    en.wikipedia.org/wiki/Prescriptive_analytics

    Prescriptive analytics is the third and final phase of business analytics, which also includes descriptive and predictive analytics. [2] [3] Referred to as the "final frontier of analytic capabilities", [4] prescriptive analytics entails the application of mathematical and computational sciences and suggests decision options for how to take advantage of the results of descriptive and ...