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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    The speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development. Big data is often available in real-time. Compared to small data, big data is produced more continually. Two kinds of velocity related to big data are the frequency of generation and the frequency of handling ...

  3. Small data - Wikipedia

    en.wikipedia.org/wiki/Small_data

    Small data is data that is 'small' enough for human comprehension. [1] It is data in a volume and format that makes it accessible, informative and actionable. [2] The term "big data" is about machines and "small data" is about people. [3] This is to say that eyewitness observations or five pieces of related data could be small data.

  4. Orders of magnitude (data) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude_(data)

    2 × 10 18 bits (250 petabytes) – storage space at Facebook data warehouse as of June 2013, [11] growing at a rate of 15 PB/month. [12] 2 61: 2,305,843,009,213,693,952 bits (256 pebibytes) 2.4 × 10 18 bits (300 petabytes) – storage space at Facebook data warehouse as of April 2014, growing at a rate of 0.6 PB/day. [13] 2 62

  5. 1 Reason to Expect Big Things from HNI - AOL

    www.aol.com/news/2013-01-25-1-reason-to-expect...

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  6. Endianness - Wikipedia

    en.wikipedia.org/wiki/Endianness

    Gulliver's Travels by Jonathan Swift, the novel from which the term was coined. In computing, endianness is the order in which bytes within a word of digital data are transmitted over a data communication medium or addressed (by rising addresses) in computer memory, counting only byte significance compared to earliness.

  7. Small vs. Large Companies: 10 Differences Between ... - AOL

    www.aol.com/news/2012-02-06-small-vs-large...

    What may be normal for a small company could be strange for a large one. But when deciding where to work, those distinctions matter. "There are a number of differences," says Kathleen Downs, a ...

  8. 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 ...

  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. [30]