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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. 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 ]

  4. Challenges with data blending - Wikipedia

    en.wikipedia.org/wiki/Data_blending

    Data blending is a process whereby big data from multiple sources [1] are merged into a single data warehouse or data set. [ 2 ] Data blending allows business analysts to cope with the expansion of data that they need to make critical business decisions based on good quality business intelligence . [ 3 ]

  5. Top 10 Big Data Stocks: Apple - AOL

    www.aol.com/2012/03/05/top-10-big-data-stocks-apple

    The following video is part of our "Motley Fool Conversations" series, in which analyst John Reeves and advisor David Meier discuss topics across the investing world.McKinsey defines "big data" as ...

  6. Data governance - Wikipedia

    en.wikipedia.org/wiki/Data_governance

    Leaders of successful data governance programs declared at the Data Governance Conference in Orlando, FL, in December 2006 that data governance is about 80 to 95 percent communication. [10] That stated, it is a given that many of the objectives of a data governance program must be accomplished with appropriate tools.

  7. Analytics - Wikipedia

    en.wikipedia.org/wiki/Analytics

    Such data sets are commonly referred to as big data. [36] Whereas once the problems posed by big data were only found in the scientific community, today big data is a problem for many businesses that operate transactional systems online and, as a result, amass large volumes of data quickly. [37] [36]

  8. 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]

  9. List of big data companies - Wikipedia

    en.wikipedia.org/wiki/List_of_big_data_companies

    Alpine Data Labs, an analytics interface working with Apache Hadoop and big data; AvocaData, a two sided marketplace allowing consumers to buy & sell data with ease. Azure Data Lake is a highly scalable data storage and analytics service. The service is hosted in Azure, Microsoft's public cloud

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