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Big Data Analytics for Industrial Application

Table of contents

Big Data Analytics for Industrial Application at Cranfield University

Language: English Studies in English
Subject area: computer science
University website: www.cranfield.ac.uk

Definitions and quotes

Analytics
Analytics is the discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
Big Data
Big data is data sets that are so voluminous and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. There are a number of concepts associated with big data: originally there were 3 concepts volume, variety, velocity. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) and value.
Data
Data ( DAY-tə, DAT-ə, DAH-tə) is a set of values of qualitative or quantitative variables.
Experimental work, data analysis and numerical modelling have provided a sound quantitative assessment of climatic change on inland seas and their regions, particularly vulnerable to climatic and anthropogenic impacts.
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