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A Business Application of the Business Intelligence and the Big Data Analytics

비즈니스 인텔리전스와 빅데이터 분석의 비즈니스 응용

  • Lee, Ki-Kwang (Department of Business Administration, Dankook University) ;
  • Kim, Tae-Hwan (Department of Business Administration, Dankook University)
  • Received : 2019.10.08
  • Accepted : 2019.11.13
  • Published : 2019.12.31

Abstract

Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It's also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business' changing requirements, if they prove to be highly valuable to business environment.

Keywords

References

  1. Chaudhuri, S., Dayal, U., and Narasayya, V., An overview of business intelligence technology, Communications of the ACM, 2011, Vol. 54, No. 8, pp. 88-98. https://doi.org/10.1145/1978542.1978562
  2. Chen, H., Chiang, H.L., and Storey, V.C., Business Intelligence and Analytics : From Big Data to Big Impact, MIS Quarterly, 2012, Vol. 36, No. 4, pp. 1165-1188. https://doi.org/10.2307/41703503
  3. Chun-Wei, T., Chin-Feng, L., Chao, H.C., and Vasilakos, A.V., Big data analytics : a survey, Journal of Big Data, 2015, Vol. 2, No. 1, pp. 1-32.
  4. Esling, P. and Argon, C., Time-Series Data Mining, ACM Computing Surveys, 2012, Vol. 45, No. 1, p. 12.
  5. George, G, Haas, M.R., and Pentland, A., Big Data and Management, Academy of Management Journal, 2014, Vol. 57, No. 2, pp. 321-326. https://doi.org/10.5465/amj.2014.4002
  6. Howson, C., Successful Business Intelligence : Secrets to Making BI the Killer App, New York-McGraw-Hill Companies, 2008
  7. Karim, R. and Alla, S., Scala and Spark for Big Data Analytics : Explore the concepts of functional, Packt Publishing Ltd., 2017.
  8. Kennedy, K., Employee Job Satisfaction and Engagement : Revitalizing a Changing Workforce, A research Report by The Society for Human Resource Management, 2016, pp. 17-18.
  9. Lanley, D., Big Data Means Big Business A research Report by The Society for Human Resource Management, Gartner Group 2012.
  10. Lanley, D., Controlling Data Volume, Velocity, and Variety, http://blogs.gartner.com/doug-laney/files/, 2012.
  11. Leandro, A., 5 Differences Between Big Data And Business Intelligence, https://thinkincredible.intraway.com/blog-post/big-data-and-business-intelligence, 2017.
  12. Martin, E., Top Five Benefits of Business Intelligence, https://vantageonesoftware.com/top-five-benefits-business-intelligence-bi, 2017,
  13. Obeidat, M., North, M., Richardson, R., and Rattanak, V.. Business Intelligence Technology, Applications, and Trends, International Management Review, 2015, Vol. 11, No. 2, p. 47.
  14. Olap.com, https://olap.com/learn-bi-olap/olap-bi-definitions/business-intelligence.
  15. Stancu, R., Big Data and Business Opportunities, Knowledge Horizons. Economics, 2019, Vol. 11, No. 2, pp. 38-43.
  16. Wamba, S.F., Angappa, G., Akter, S., Ren, S.J., Dubey, R., and Childe, S., Big data analytics and firm performance : Effects of dynamic capabilities, Journal of Business Research, 2017, Vol. 70, pp. 356-365. https://doi.org/10.1016/j.jbusres.2016.08.009
  17. Williams, M., Ariyachandra, T., and Frolick, M., Business Intelligence-Success Through Agile Implementation, Journal of Management & Engineering Integration, 2017, Vol. 10, No. 1, pp. 14-21.
  18. Wu, X. and Ding, W., Data mining with big data, IEEE Transactions on Knowledge and Data Engineering, 2014, Vol. 26, No. 1, pp. 97-107. https://doi.org/10.1109/TKDE.2013.109
  19. Yu, J.D. and Lee, I.S., A Prediction of Stock Price Through the Big-data Analysis, Journal of Society of Korea Industrial and Systems Engineering, 2018, Vol. 41, No. 3, pp. 97-107. https://doi.org/10.11627/jkise.2018.41.3.097