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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. [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]
This maturity model is prescriptive in the sense that the model consists of four distinct phases that each plot a path towards big data maturity. Phases are: Phase 1, undergo big data education; Phase 2, assess big data readiness; Phase 3, pinpoint a killer big data use case; Phase 4, structure a big data proof-of-concept project [11]
In the fields of Information Technology (IT) and Systems Management, IT operations analytics (ITOA) is an approach or method to retrieve, analyze, and report data for IT operations. ITOA may apply big data analytics to large datasets to produce business insights. [1] [2] In 2014, Gartner predicted its use might increase revenue or reduce costs. [3]
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]
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. [40]
Analytics is the application of mathematics and statistics to big data. Data scientists write analytics programs to look for solutions to business problems, like forecasting demand or setting an optimal price. The continuous approach runs multiple stateless engines which concurrently enrich, aggregate, infer and act on the data.
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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]