Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Bigdata Analysis Project Development Methodology

빅데이터 분석 프로젝트 수행 방법론

  • Received : 2014.01.16
  • Accepted : 2014.02.06
  • Published : 2014.03.31
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Abstract

As the importance of big data analysis increases to improve the competitiveness of a corporate, a unified big data project development methodology is required in order to study the problem of a corporate in a systematic way and evaluate the problem w.r.t. a business value after solving the problem. This paper propose Scientific Data Anslysis and Development methodology(SDAD) which are integrated methodology of software development and project management for easier application into a field project. SDAD consisits of 6 stages(problem definition stage, data preparation stage, model design stage, model development stage, result extraction stage, service development state), each stages has detailed processes(47) and productions(93). SDAD, furthermore, unified previous ISP, DW, SW development methodologies in terms of the data analysis and can easily interchange the productions with them. This paper, lastly, introduces a way to assign responsible persons for each process and provide communication procedures in RACI chart to improves the efficiency of the interaction among professionals from different subjects. SDAD is applied to a Bigdata project in Korea Employment Information Services institution and the result turned out to be acceptable when evaluated by the supervision.

기업 경쟁력 제고를 위해 빅데이터 분석의 중요성이 대두됨에 따라, 기업의 문제점을 체계적으로 파악하고 이를 해결하여 사업적 가치로 재평가하기 위해서는 통합적 빅데이터 프로젝트 수행 방법이 필요하다. 이에 따라 실무적 활용 용이성을 높이도록 소프트웨어 개발과 프로젝트 관리가 융합된 "과학적 데이터 분석 방법론(SDAD)"를 제안한다. SDAD는 프로젝트 수행 과정을 문제정의, 데이터준비, 모델설계, 모델구현, 결과평가, 서비스구현의 6단계를 구성한 후, 단계별 과업을 공정별(47개)로 세분화하고 산출물(93개)을 도출한다. SDAD 는 기존의 ISP, DW, SW 개발 방법론에서 빅데이터 분석과 관련된 부분을 통합하고 쉽게 결과물을 연동할 수 있도록 하였다. 또한, 다양한 분야의 전문가로 구성된 참여자 간에 의사소통의 효율성을 높이기 위해 RACI 챠트를 통해 공정별 책임자를 할당하는 방법과 표준화된 의사소통 절차를 제시한다. SDAD 방법론은 한국고용정보원에서 수행한 빅데이터 프로젝트에 적용하여 감리의 평가를 받은 결과 적정한 것으로 나타났다.

Keywords

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