A Study on Real-Time Business Intelligence and Big Data

Ms.P.R.S.M.Lakshmi ； Ms.K.SanthiSri ； Mr.N.Veeranjaneyulu

《Information Engineering》 4卷 (2015/03) Pp. 1-6

https://doi.org/10.14355/ie.2015.03.001

並列摘要

Most of the organizations is deploying Business Intelligence (BI) for optimizing every day business operations from past few years. As far as this operational BI approach has been consummate mainly by sinking the latency of data integration and data analysis tasks in traditional enterprise Data Warehousing systems. While sinking these latencies allow earlier to Real-Time (RT) analysis of business operations, it does not support Real-Time decisions to be completed on Real-Time data, i.e., it does not support Real- Time operational BI. Yet, few organizations have recognized their need for RT operational BI. Still anywhere they have, the convolution and costs have often been too lofty. The arrival of big data, though, changes the situation radically. Big data is a shoddily defined and hackneyed term, but, to us, it represents not only new sources of data that aid the analysis and optimization business operations, but also the advances in the erudition and supremacy of analytic techniques. It also reflects the significant advances made by vendors in reducing the costs and improving the performance of analytic software and hardware platforms. Big data increases the number of use cases for RT operational BI and, given the improvements in the price/performance of analytic processing, this makes RT processing viable for a mounting number of organizations. In this paper, we explore the use cases for RT operational BI in the epoch of big data, examine the technologies that enable RT operational BI, and discuss how the traditional Enterprise Data Warehouse (EDW) environment can be extended to support both RT processing and Big Data.

並列關鍵字

Erudition ； Convolution ； Shoddily