DocumentCode :
725777
Title :
Embrace the Challenges: Software Engineering in a Big Data World
Author :
Anderson, Kenneth M.
Author_Institution :
Dept. of Comput. Sci., Univ. of Colorado, Boulder, CO, USA
fYear :
2015
fDate :
23-23 May 2015
Firstpage :
19
Lastpage :
25
Abstract :
The design and development of data-intensive software systems -- systems that generate, collect, store, process, analyze, query, and visualize large sets of data -- is fraught with significant challenges both technical and social. Project EPIC has been designing and developing data-intensive systems in support of crisis informatics research since Fall 2009. Our experience working on Project EPIC has provided insight into these challenges. In this paper, we share our experience working in this design space and describe the choices we made in tackling these challenges and their attendant trade-offs. We highlight the lack of developer support tools for data-intensive systems, the importance of multidisciplinary teams, the use of highly-iterative life cycles, the need for deep understanding of the frameworks and technologies used in data intensive systems, how simple operations transform into significant challenges at scale, and the paramount significance of data modeling in producing systems that are scalable, robust, and efficient.
Keywords :
Big Data; software engineering; Big Data; Project EPIC; crisis informatics research; data-intensive software system design; data-intensive software system development; data-intensive system design; data-intensive system development; highly-iterative life cycles; large-data-set analysis; large-data-set collection; large-data-set generation; large-data-set processing; large-data-set query; large-data-set storage; large-data-set visualization; multidisciplinary teams; social aspect; software engineering; technical aspect; Big data; Data models; Relational databases; Reliability; Software systems; Twitter; big data; data-intensive software systems; design challenges;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data Software Engineering (BIGDSE), 2015 IEEE/ACM 1st International Workshop on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/BIGDSE.2015.12
Filename :
7166054
Link To Document :
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