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Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [25] 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. [26]
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 ...
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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International scientific open access bibliography for theology and religious studies. The IxTheo lists monographs, collected works, journals, essays, encyclopaedia articles, reviews as well as databases, archive materials, literary remains, blogs, podcasts, research data and other electronically available content from all fields of theology.
Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]
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]
Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...