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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 ecosystem - Wikipedia

    en.wikipedia.org/wiki/Data_ecosystem

    The rise of data ecosystems is part and parcel with the development of big data. Big data is an emerging trend in science and technology that tracks and defines almost all human engagement. [10] It is defined by the following five properties:

  4. Data-intensive computing - Wikipedia

    en.wikipedia.org/wiki/Data-intensive_computing

    The fundamental challenges for data-intensive computing are managing and processing exponentially growing data volumes, significantly reducing associated data analysis cycles to support practical, timely applications, and developing new algorithms which can scale to search and process massive amounts of data.

  5. Critical data studies - Wikipedia

    en.wikipedia.org/wiki/Critical_data_studies

    Critical data studies is the exploration of and engagement with social, cultural, and ethical challenges that arise when working with big data. It is through various unique perspectives and taking a critical approach that this form of study can be practiced. [ 1 ]

  6. 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.

  7. Data economy - Wikipedia

    en.wikipedia.org/wiki/Data_economy

    Big data is defined as the algorithm-based analysis of large-scale, distinct digital data for purposes of prediction, measurement, and governance. [6] [7] This involves processing vast amounts of information from various sources, like social media, sensors, or online transactions, using advanced computer programs (algorithms).

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  9. Data divide - Wikipedia

    en.wikipedia.org/wiki/Data_divide

    Using the framework of the digital divide, the data divide posits that the evolving nature of data and big data has created divisions and inequalities in data ownership, access, analysis, collection, and the manipulation of personal data generated by information and communications technologies (ICTs). [1]