IMPROVING DATA ANALYSIS THROUGHDIVERSE DATA SOURCEINTEGRATION
Ronald Albuquerque, Jennifer L. Casper, Ed Cheung, Ronald G. Couture, Barry Chi Hong Lai, Peter Leveille, Jing Zhu Hu, Dan Mauer · 2009
Daily sensor data volumes are increasing from gigabytes to multiple terabytes. The manpower and resources needed to analyze the increasing amountofdata are not growing at the same rate. Current volumesof diverse data, both live streaming and historical, are not fully analyzed. Analysts are left mostly to analyzing the individual data sources manually. This is both time consuming and mentally exhausting. Expanding data collections only exacerbate this problem. Improved data management techniques and analysis methods are required to process the increasing volumesof historical and live streaming data sourcessimultaneously. Analysts need improved techniques to reduce an decision response time and to enable more intelligent and immediate situation awareness. Faster analysis of disparate information sources may be achieved by providing a system that allows analysts to pose integrated queries on diverse data sources without losing data provenance.