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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    A 2011 McKinsey Global Institute report characterizes the main components and ecosystem of big data as follows: [52] Techniques for analyzing data, such as A/B testing, machine learning, and natural language processing; Big data technologies, like business intelligence, cloud computing, and databases

  3. Data processing - Wikipedia

    en.wikipedia.org/wiki/Data_processing

    Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.

  4. Lambda architecture - Wikipedia

    en.wikipedia.org/wiki/Lambda_architecture

    Flow of data through the processing and serving layers of a generic lambda architecture. Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch and stream-processing methods.

  5. Journal of Big Data - Wikipedia

    en.wikipedia.org/wiki/Journal_of_Big_Data

    Journal of Big Data is a scientific journal that publishes open-access original research on big data.Published by SpringerOpen since 2014, it examines data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing ...

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is an interdisciplinary academic field [1] that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge and insights from potentially noisy, structured, or unstructured data.

  7. Data-intensive computing - Wikipedia

    en.wikipedia.org/wiki/Data-intensive_computing

    Computer system architectures which can support data parallel applications were promoted in the early 2000s for large-scale data processing requirements of data-intensive computing. [12] Data-parallelism applied computation independently to each data item of a set of data, which allows the degree of parallelism to be scaled with the volume of data.

  8. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...

  9. 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.