Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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A Study on the Effective Approaches to Big Data Planning

효과적인 빅데이터분석 기획 접근법에 대한 융합적 고찰

  • Received : 2014.11.05
  • Accepted : 2015.01.20
  • Published : 2015.01.28
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Abstract

Big data analysis is a means of organizational problem solving. For an effective problem solving, approaches to problem solving should take into account the factors such as characteristics of problem, types and availability of data, data analytic capability, and technical capability. In this article we propose three approaches: logical top-down, data driven bottom-up, and prototyping for overcoming undefined problem circumstances. In particular we look into the relationship of creative problem solving with the bottom-up approach. Based on the organizational data governance and data analytic capability, we also derive strategic issues concerning the sourcing of big data analysis.

빅데이터분석은 조직의 문제해결을 위한 융합적 수단이다. 효과적인 문제해결을 위해서는 문제의 형태, 데이터의 유형 및 존재여부, 데이터 분석역량, 분석을 위한 기반정보기술의 수준 등 다양한 요인을 융합적으로 고려하여 문제해결의 접근법이 결정되어야 한다. 본 연구에서는 기획 접근법으로 논리적인 하향식 접근법, 데이터기반의 상향식 접근법, 그리고 문제해결 환경의 불확실성을 극복하기 위한 프로토타이핑 접근법 등 세 가지 유형을 제안한다. 특히, 이 유형 중에서 창의적 문제해결과 상향식 접근법이 어떤 연관성을 갖는지 살펴본다. 또한 데이터 거버넌스와 데이터 분석역량을 융합적으로 고려하여 조직의 빅데이터분석의 소싱과 관련한 주요 전략적 이슈를 도출한다.

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