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A Study on Possible Construction of Big Data Analysis System Applied to the Offline Market

오프라인 마켓에 적용 가능한 빅데이터 분석 시스템 구축 방안에 관한 연구

  • Lee, Hoo-Young (Dept. of Multimedia, Kongju National University) ;
  • Park, Koo-Rack (Dept. of Computer Science & Engineering, Kongju National University) ;
  • Kim, Dong-Hyun (Dept. of IT Convergence, Woosong University)
  • 이후영 (공주대학교 멀티미디어공학과) ;
  • 박구락 (공주대학교 컴퓨터공학부) ;
  • 김동현 (우송대학교 IT융합학부)
  • Received : 2016.07.06
  • Accepted : 2016.09.20
  • Published : 2016.09.28

Abstract

Big Data is now seen as a major asset in the company's competitiveness, its influence in the future is expected to grow. Companies that recognize the importance are already actively engaged with Big Data in product development and marketing, which are increasingly applied across sectors of society, including politics, sports. However, lack of knowledge of the system implementation and high costs are still a big obstacles to the introduction of Big Data and systems. It is an objective in this study to build a Big Data system, which is based on open source Hadoop and Hive among Big Data systems, utilizing POS sales data of small and medium-sized offline markets. This approach of convergence is expected to improve existing sales systems that have been simply focusing on profit and loss analysis. It will also be able to use it as the basis for the decisions of the executive to enable prediction of the consumption patterns of customer preference and demand in advance.

빅데이터는 현재 기업 경쟁력의 주요 자산으로 여겨지고 있고 향후에 그 영향력은 더욱 확대될 것으로 전망된다. 그 중요성을 인식한 기업들은 이미 빅데이터를 제품 개발과 마케팅에 적극적으로 활용하고 있으며 정치, 스포츠 등 사회 전반에 걸쳐 적용분야는 점점 늘어나고 있다. 그러나 시스템 구축에 따른 노하우 부족과 고비용은 빅데이터 시스템 도입에 여전히 큰 장애가 되고 있다. 본 논문에서는 중소규모 오프라인 마켓의 POS 판매 데이터를 빅데이터 시스템 중 오픈소스인 하둡(Hadoop) 및 하이브(Hive)를 기반으로 하는 빅데이터 시스템 구현을 목표로 한다. 이러한 융복합을 통해 단순히 손익분석과 재고관리 등에 집중되었던 기존 판매 시스템을 보완하여 고객의 소비패턴과 선호도 조사, 수요에 대한 사전 예측이 가능하도록 하는 경영자의 합리적인 의사결정에 기초자료로 활용할 수 있을 것으로 기대된다.

Keywords

References

  1. Q. Y. Hao, S. J. Lee, K. R. Lee, "The Acceptance of Customer Reviews in Taobao", Journal of the Korea Convergence Society, Vol. 6, No. 4, pp. 205-212, 2015. https://doi.org/10.15207/JKCS.2015.6.4.205
  2. S. H. Park, I. H. Lee, H. Y. Ahn, "Analysis of the Retail Channels Resulting from Changing Consumption Trends", Hana Institute of Finance, No. 13, 2009.
  3. G. D. Seo, J. E. Lee, "A study on the Effect of Consumer Lifestyle on Brand Attitude, Brand Attachment influence upon Brand Loyalty", Journal of Digital Convergence, Vol. 14, No. 4, pp. 185-192, 2016.
  4. K. W. Ko, D. C. Kim, "The Analyses of the Operational Efficiency and Efficiency Factors of Retail Stores Using DEA Model," Korean Management Science Review, Vol. 31, No. 4, pp. 135-150, 2014. https://doi.org/10.7737/KMSR.2014.31.4.135
  5. K. C. Ahn, et al.,"POS Data Analysis System based on Association Rule Analysis", Korea Society of Industrial Information Systems, Vol. 17, No. 5, pp. 9-17, 2012.
  6. James Dyson, "Paperless Receipt Solution (PRS) System", James Dyson Foundation, 2015.
  7. O. B. Kwon, H. C. Shin, "Mobile Point-of-Sales System", Journal of Information and Security, Vol 7, No. 3, pp. 87-93, 2007.
  8. K. C. Ahn, et al,, "POS Data Analysis System based on Association Rule Analysis", Journal of the Korea Industrial Information System Society , Vol. 17, No. 5, pp. 9-17, 2012.
  9. Y. S. Jeong, Y. T. Kim, G. C. Park,, "Subnet Selection Scheme based on probability to enhance process speed of Big Data", Journal of Digital Convergence, Vol. 13, No. 9. pp. 201-208, 2015.
  10. S. H. Namn, K. S. Noh, "A Study on the Effective Approaches to Big Data Planning", Journal of Digital Convergence, Vol. 13, No. 1, pp. 227, 235, 2015.
  11. K. S. Noh, S. T. Park, K. H. Park, "Convergence Study on Big Data Competency Reference Model", Journal of Digital Convergence, Vol. 13, No. 3, pp. 55-63, 2015. https://doi.org/10.14400/JDC.2015.13.3.55
  12. B. C. Kim, "A study on Utilization of Big Data Based on the Personal Information Protection Act", Journal of Digital Convergence, Vol. 13, No. 12, pp. 87-92, 2014.
  13. K. C. Choi, J. A. Yoo, "A reviews on the social network analysis using R", Journal of the Korea Convergence Society, Vol. 6, No. 1, pp. 77-83, 2015. https://doi.org/10.15207/JKCS.2015.6.1.077
  14. G. S. Hang, "Big Data Platform Strategy: Big Data is Changing Business Platform Future Revolution", Electronic Times, pp. 83-97, 101-105, 193-203, 2013.
  15. http://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html
  16. J. H. Kwak, et al., "Large-scale Data Analysis based on Hadoop for Astroinformatics", Journal of KIISE, Vol. 17, No. 11, pp. 587-591, 2011.
  17. http://hci.stanford.edu/courses/cs448g/a2/files/map_reduce_tutorial.pdf
  18. Venner, Jason, "Pro Hadoop", Apress, 2009.
  19. Y. H. Lee, Y. S. Lee, "Yet Another BGP Archive Forensic Analysis Tool Using Hadoop and Hive", Journal of KIISE, Vol. 42, No. 4, pp. 541-549, 2015. https://doi.org/10.5626/JOK.2015.42.4.541
  20. Apache Hive: https://cwiki.apache.org/confluence/display/hive/Design