Keyword

Big data, data governance, data governance framework, case analysis

Abstract

          Information services based on Big Data analytics require data governance that can satisfy needs for corporate governance. While existing data governance focuses on data quality but Big Data governance needs to be established in consideration of a broad sense of Big Data services such as analysis of social trends and predictions of change. To achieve goals of Big Data services, strategies need to be established with alignment to the vision of the corporation. For successful implementation of Big Data services, there is needed a framework to enable initiation ofa Big Data project as a guide and method. We propose the Big Data Governance Framework to facilitate successful implementation in this study.
           Big Data governance framework presents additional criteria from existing data governance focused on data quality level. The Big Data governance framework focuses on timely, reliable, meaningful, and sufficient data services. The objective of Big Data services is what data attributes should be achieved based on Big Data analytics. In addition to the quality level of Big Data, personal information protection strategy and data disclosure/accountability strategy are needed to prevent problems.
          This study conducted case analysis about the National Pension Service (NPS) of South Korea based on the Big Data Governance Framework we propose. Big Data services in the public sector are an inevitable choice to improve quality of life of people. Big Data governance and its framework are essential components for the realization of Big Data services’ success. In case-analyses, we identified vulnerabilities or risk areas, and we hope that these case studies will be used as major references to implement Big Data services without problems.


Full Text : PDF

References
  1. Bizer, C., Boncz, P., Brodie, M. L., Erling, O., (2012)” The Meaningful Use of Big Data: Four Perspectives – Four Challenges”, SIGMOD Record, Vol. 40, No. 4, pp.56-60
  2. Boyd, D., Crawford, K., (2011) “Six Provocations for Big Data”, SSRN eLibrary.
  3. Edjlali, R. & Friedman, T., (2011) “Data quality for Big Data: Principles remain, but tactics change” Gartner
  4. Gantz, J., David R., (2011) "Extracting value from chaos." IDC review 1142: 9-10.
  5. IT Governance Institute, Board Briefing on IT Governance, 2nd ed., Rolling Meadows, IL, pp.6-7.
  6. Jung, Y., (2012) “Big Data Revolution and Media Policy Issues,” KISDI Premium Report, 12(2)
  7. Lee, S., (2013), “National Pension Service of Korea, preparing the base of BigData Analysis … Consulting and Pilot is On,” Digital Daily, 2013.11.23. http://www.ddaily.co.kr/news
  8. Kim, B. (2012) “Smart Era, Data Protection Strategy and the Law II”, Korea Academy Information, Kyunggido(Korea)
  9. Kim, H. Y., (2013) “Data Governance for Big Data and Medical Information Service practice”, Information System Audit and Control, Vol. 25, pp.18-27.
  10. Kim, S., (2011) “A Case Study of Implementation Data Governance for Enterprise Architecture,” Journal of Information Technology and Architecture, Vol. 8. No. 3, pp.255-265
  11. Kim, S., (2013) “The Analysis of Data Governance model for Business and IT Alignment,” Journal of The Korea Society of Computer and Information, Vol. 18, No. 7, pp.69-78.
  12. KIPA (Korea Internet and Security Agency), (2008) “The importance of data governance and data quality management”, SW Industry trend, Oct.
  13. Kumar, S., (2008) “Data governance: An approach to effective data management.” White paper, Satyam Computer Services, Ltd.
  14. Lee, J., (2012) "Data Big bang, the trend of Big Data” Journal of Communications & Radio Spectrum, vol. 47, pp.43-55.
  15. Lee, K. Y., Nam, G. H., Sim J., Cho, G., Ryu, W., (2012) “Construction of Knowledge Base for The Utilization of Big Data in Public Domain” Communications of the Korea Information Science Society 30(6), pp.40-46
  16. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big Data: The next frontier for innovation, competition, and productivity.
  17. Monks, R. A. G., Minow, N., (2008). Corporate Governance, Chichester, England: John Wiley and Sons Ltd, p.14.
  18. Panian, Z., (2010)” Some Practical Experiences in Data Governance”, World Academy of Science, Engineering and Technology.
  19. Power, D., (2011)” A 4-D Approach to Data Governance”, Information Management, May, pp.29-30.
  20. Price, R. & Shanks, G. (2005) “A semiotic information quality framework: development and comparative analysis”, Journal of Information Technology, 2005(20), pp.88-102.
  21. Shankaranarayan, G., Ziad, M., Wang, R. Y., (2003) “Managing Data Quality in Dynamic Decision Environments: An Information Product Approach”, Journal of Database Management, 14(4), pp.14-32.
  22. Smith, M., Szongott, C., Henne, B., Voigt, G. V., (2012) “Big Data Privacy Issues in Public Social Media”, 2012 6th IEEE International Conference, June, pp.18-20.
  23. Thomas, G., (2006) "The DGI data governance framework." The Data Governance Institute, Orlando, FL (USA)
  24. Wende, K., (2007) “A model for data governance-organization accountabilities for data quality management”, 18thAustralasian Conference on Information Systems, Toowoomba. pp.417-424.