PENGARUH KUALITAS DATA TERHADAP MANFAAT YANG DIPEROLEH DARI IMPLEMENTASI DATA WAREHOUSE

Munawar Munawar

Sari


Given that the literature indicates that many benefits can be obtained from a DW (data warehouse), but that the threat of failure is also high, therefore more understanding of the quality dimensions that contribute to the success of a DW is required. This study address that need through an empirical investigation of success in data warehousing as measured by DQ (data quality) dimensions involvement in every stage of DW development. This study attempts to confirm DW benefits from reviewed literature in five case studies and three consultants. This study also identifies relationship amongst DQ dimensions in DW development stages and DW success. This study is helpful for DW practitioners, implementers and researchers for understanding of the challenges which DQ dimensions in DW stages are significant to establishing a successful DW development.
Keywords: data warehouse, data quality, data warehouse benefits.
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Agosta, L. (2004). Data Warehousing Lessons Learned: A Time of Growth for Data Warehousing, in DM Review Magazine, 2004, pp. Retrieved on 29/3/2011, from http://www.dmreview.com/article_sub.cfm?articleId=1012461.

Agrawal, D. (2008). The Reality of Real-Time Business Intelligence in Business Intelligence for the Real-Time Enterprise. Second International Workshop, BIRTE 2008, Auckland, New Zealand, August 24, 2008, Revised Selected Papers. Lecture Notes in Business Information Processing, pp. 75-88.

Al-Debei, M.M. (2011). Data Warehouse as a Backbone for Business Intelligence. European Journal of Economics, Finance, and Administrative Sciences, 33, 153-166.

Alshawi, S., Saez-Pujol, I. and Irani, Z. (2003). Data warehousing in decision support for pharmaceutical R & D supply chain. International Journal of Information Management, 23, 259-268. http://dx.doi.org/10.1016/S0268-4012(03)00028-8.

Amornbuth, C. (2015). The Relationship of the Quality Data Warehousing to Enhanced Perceived Net Profits and Decision Quality in the Enterprises. Universal Journal of Management 3(12): 514-520. DOI: 10.13189/ujm.2015.031206.

Bilal Ali, Y. A. (2014). Challenges in the Successful Implementation of Data Warehouse. Journal of Management Research. ISSN 1941-899X. 2014. Vol 6, No 3.

Coleho, P.S. and Esteves, S.P. (2007). The choice between a 5-point and 10-point scale in the framework of customer satisfaction measurement. International Journal of Market Research, Vol. 49. No. 3, 2007, pp.313-345.

Flyvberg, B. (2006). Five misunderstandings about case study research. Qualitative Inquiry 12, 2, 219-245.

Friedman, T. (2004). Data Quality ‘Firewall’ Enhances Value of the Data Warehouse. Gartner Reports, Apr. 2004.

Griffin, R. K. (1998). Data Warehousing. Cornell Hospitality Quarterly, 39, 28-35.

Hwang, M. I., & Xu, H. (2008). A Structural Model of Data Warehousing Success. Journal of Computer Information Systems, 49(1).

Haug, A., Zachariassen, F and Van Liempd, D. (2011). The Costs of Poor Data Quality. Journal of Industrial Engineering and Management (JIEM 2011), 4(2): 168-193.

Joseph, M.V. (2013). Significance of Data Warehousing and Data Mining in Business Applications. International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-3, Issue-1, March 2013.

Kumar, V. and Thareja, R. (2013). A Simplified Approach for Quality Management in Data Warehouse. International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.3, No.5, September 2013.

Mukherjee, D. (2003). An empirical investigation of critical factors that influence data warehouse implementation success.

MajidZaman, E., Quadri, S.M.K., and But, M. A. (2012). Information Integration for Heterogeneous Data Sources. IOSR Journal of Engineering Apr. 2012, Vol. 2(4) pp: 640-643. ISSN: 2250-3021.

Munawar. (2016). Fase-Fase yang Umum Digunakan dalam Pembangunan Data Warehouse dan Kualitas Data yang Harus Dipertimbangkan di Setiap Fasenya. Jurnal Ilmu Komputer.

Pandey, A. and Mishra, S. (2014). Moving from Traditional Data Warehouse to Enterprise Data Management : a Case Study. Issues in Information Systems Volume 15, Issue II, pp. 133-140, 2014.

Rahman, N., Marz, J., and Akhter, S. (2012). An ETL Metadata Model for Data Warehousing. Journal of Computing and Information Technology - CIT 20, 2012, 2, pp. 95–111. doi:10.2498/cit.1002046.

Ranjit Singh and Kawaljeet Singh. (2010). A Descriptive Classification of Causes of Data Quality Problems in Data Warehousing. IJCSI International Journal of Computer Science Issues. Vol. 7, Issue 3, No 2 May 2010. ISSN : 1694-0784.

Rudra, A and Yeo, E. (2000). Issues in User Perceptions of Data Quality and Satisfaction in Using a Data Warehouse - An Australian Experience, Proceedings of the 33rd Hawaii International Conference on System Sciences, IEEE 2000, pp. 1-7.

Shahzad, M.K. (2012). Improving Business Processes using Processoriented Data Warehouse. Doctoral Dissertation in Computer and Systems Sciences School of Information and Communication Technologies KTH - Royal Institute of Technology, Stockholm, Sweden.

Stake, R. E. (1995). The Art of Case Study Research, London: SAGE.

Tellis, W. (1997). Introduction to case study. The Qualitative Report, 3 (2), 1-11.

Torlone, R. (2008). Two Approaches to the Integration of Heterogeneous Data Warehouses. Distrib. Parallel Databases 23(1), pp. 69–97.

Watson, H.J. and Haley, B.J. (1997). Data warehousing: a framework and survey of current practices, Journal of Data Warehousing 2 (1) (1997) 10–17.

Watson, H. J., Goodhue, D. L. and Wixom, B. H. (2002). The benefits of data warehousing: why some organizations realize exceptional payoffs. Information and Management, vol. 39, pp. 491-502.

Watson, H. and Haley, B. (1998). A Structural Model of Data Warehousing Success. Journal of Data Warehousing, 2, 10-17.

Winter, R and Strauch, B. (2003). A method for demand-driven information requirements analysis in data warehousing. In Proceedings of Hawaii International Conference on System Sciences, Hawaii, 1359-1365.

Wixom, B. H. and Watson, H. J. (2001). An Empirical Investigation of the Factors Affecting Data Warehousing Success. MIS Quarterly, vol. 25, pp. 17-41.




DOI: https://doi.org/10.47007/komp.v2i02.2190

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