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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    The term big data has been in use since the 1990s, with some giving credit to John Mashey for popularizing the term. [22] [23] Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.

  3. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).

  4. Big Ideas Learning - Wikipedia

    en.wikipedia.org/wiki/Big_Ideas_Learning

    Ron Larson, Text and Academic Authors Association Most Promising New Textbook Award, 2013, Big Ideas Math: A Common Core Curriculum Algebra 1, 1st Edition (Big Ideas Learning) Ron Larson, Text and Academic Authors Association Textbook Excellence Award, 2014, Big Ideas Math: A Common Core Curriculum , 7 Book Series, 2nd Edition, (Big Ideas ...

  5. Analytical skill - Wikipedia

    en.wikipedia.org/wiki/Analytical_skill

    Data analysis is a systematic method of cleaning, transforming and modelling statistical or logical techniques to describe and evaluate data. [44] Using data analysis as an analytical skill means being able to examine large volumes of data and then identifying trends within the data.

  6. Mathematical statistics - Wikipedia

    en.wikipedia.org/wiki/Mathematical_statistics

    The data from a study can also be analyzed to consider secondary hypotheses inspired by the initial results, or to suggest new studies. A secondary analysis of the data from a planned study uses tools from data analysis, and the process of doing this is mathematical statistics. Data analysis is divided into:

  7. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data. In contrast, data mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large ...

  8. 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]

  9. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1]