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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. File:Resume.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Resume.pdf

    Original file (1,275 × 1,650 pixels, file size: 53 KB, MIME type: application/pdf) This is a file from the Wikimedia Commons . Information from its description page there is shown below.

  4. Platform engineering - Wikipedia

    en.wikipedia.org/wiki/Platform_engineering

    Platform engineering is a software engineering discipline focused on the development of self-service toolchains, services, and processes to create an internal developer platform (IDP). [1] The shared IDP can be utilized by software development teams, enabling them to innovate.

  5. Data as a service - Wikipedia

    en.wikipedia.org/wiki/Data_as_a_service

    Service-oriented architecture (SOA) and the widespread use of APIs have rendered the platform on which the data resides as irrelevant. [3] Data as a service as a business model is a concept when two or more organizations buy, sell, or trade machine-readable data in exchange for something of value. [4]

  6. DataOps - Wikipedia

    en.wikipedia.org/wiki/Dataops

    DataOps is a set of practices, processes and technologies that combines an integrated and process-oriented perspective on data with automation and methods from agile software engineering to improve quality, speed, and collaboration and promote a culture of continuous improvement in the area of data analytics. [1]

  7. Data engineering - Wikipedia

    en.wikipedia.org/wiki/Data_engineering

    Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.

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  9. Microsoft Azure - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Azure

    Azure HDInsight [31] is a big data-relevant service that deploys Hortonworks Hadoop on Microsoft Azure and supports the creation of Hadoop clusters using Linux with Ubuntu. Azure Stream Analytics is a Serverless scalable event-processing engine that enables users to develop and run real-time analytics on multiple streams of data from sources ...

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