Some key problems of data management in army data engineering based on big data | IEEE Conference Publication | IEEE Xplore

Some key problems of data management in army data engineering based on big data


Abstract:

This paper analyzed the challenges of data management in army data engineering, such as big data volume, data heterogeneous, high rate of data generation and update, high...Show More

Abstract:

This paper analyzed the challenges of data management in army data engineering, such as big data volume, data heterogeneous, high rate of data generation and update, high time requirement of data processing, and widely separated data sources. We discussed the disadvantages of traditional data management technologies to deal with these problems. We also highlighted the key problems of data management in army data engineering including data integration, data analysis, representation of data analysis results, and evaluation of data quality.
Date of Conference: 10-12 March 2017
Date Added to IEEE Xplore: 23 October 2017
ISBN Information:
Conference Location: Beijing, China
Citations are not available for this document.

I. Introduction

The current information society has entered the era of big data. In March 2012, the United States government issued a “big data research and development initiative” [1], launched a $200 million investment big data development plans. The U. S. government's plan is seen as another major move in the field of information after the u.s‥ Big data, referred to by the conventional software tools in a certain range of time capture, management and processing of data, is the need for new processing mode to have a stronger decision-making ability, insight discovery and process optimization capabilities of massive, high rates of growth and diversification of information assets. Big data 5V features (IBM): Volume (large), Velocity (high speed), Variety (diversity), Value (low value density), Veracity (authenticity).

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Cites in Papers - IEEE (6)

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Cites in Papers - Other Publishers (2)

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