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Big-data applications in the government sector

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Published:01 March 2014Publication History
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Abstract

In the same way businesses use big data to pursue profits, governments use it to promote the public good.

References

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  1. Big-data applications in the government sector

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                        Reviews

                        Ganapathy Mani

                        Big data analysis is used in both public and private sectors. This article aims to differentiate between the uses of big data analytics in these sectors. The authors argue that, compared to the private sector application of big data, the public sector may need a new set of strategies to implement big data applications. The authors make an obscure comparison of public and private sector attributes. For decision making, for example, the authors attribute short-term decision making to the private sector and long-term decision making to the public sector. But, in reality, both short- and long-term decision making can be applied to both public and private sectors. Likewise, the authors generalize that government applications only apply to a large segment of the population, whereas they can affect a narrow segment of the population in much the same way as a private company (for example, a particular department within the government). The article provides a detailed analysis of the big data practices of governments across several countries, from the US to Australia, and includes proposals such as real-time analysis and global collaboration to improve and increase big data analysis to benefit the public. Although the article is well written and includes an extensive analysis, it would have had farther-reaching implications if the authors had considered more inclusive attribute classification between private and public sectors. Online Computing Reviews Service

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                        • Published in

                          cover image Communications of the ACM
                          Communications of the ACM  Volume 57, Issue 3
                          March 2014
                          99 pages
                          ISSN:0001-0782
                          EISSN:1557-7317
                          DOI:10.1145/2566590
                          • Editor:
                          • Moshe Y. Vardi
                          Issue’s Table of Contents

                          Copyright © 2014 ACM

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                          New York, NY, United States

                          Publication History

                          • Published: 1 March 2014

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