文章基本信息

标题：Meta data driven Big Data Analytics Big Data Solution for Data Mining and Warehousing
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作者：Dr. Murugan A ; Ganesan S
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2018
卷号：7
期号：4
页码：3720
DOI：10.15680/IJIRSET.2018.0704076
出版社：S&S Publications
摘要：World statistical indicators prove analytics value of 3.7 billion internet users, 4.9 billion unique mobileusers, and 2.8 billion active social media users. Denominator is with 7.4 billion world population data. In turn, theamount of business data has grown steadily every year in digital formats. In essence, collecting many diverse types ofdata very quickly does not create value. This paper is on need of analytics to uncover insights that will help thebusiness.Big data analysis is a continuum, not an isolated set of activities. There are five key approaches to analyzing bigdata and generating insight. They are Discovery tools, BI tools, In-Database Analytics, Pre-processing Hadoop andDecision Management. This powerful analytic environment offers a tremendous range of capabilities of security,scalability, and performance. It includes data mining tools to create complex models and deploy them on very largedata sets. The results of these predictive models leveraged within Business Intelligence (BI) applications. Big DataAnalytics has four levels namely Descriptive, Diagnostic, Predictive and Prescriptive. They show the value differencewith the degree of human input, auto decision and action. Our work is related to drive Big Data analytic by meta-datadesign. It is an extension of our earlier research on Meta Data Driven Enterprise Data Hub.
关键词：Big Data; Analytic; Mining; Predictive; Meta data; Prescriptive.