Implementation of Sales Executive Dashboard for A Multistore Company in Yogyakarta - Halim Budi Santoso; Priyanka Ayu Sonia Putri; Budi Sutedjo Dharma Oetomo (IJNMT (International Journal of New Media Technology), 2017)
Information Technology is a part of strategic part for enterprise strategic planning. Information Technology can help the enterprise to determine its strategic planning. Through data from the past, thecompany can learn something and help to decide some strategic issue. A Multistore Company in Yogyakarta has more than five stores. The problem raises to generate real-time sales reporting. Sales manager and owner do not have access to real-time sales condition. To ease management analyzing and reporting sales condition, dimension model of the sales data needs to be built. This dimension model will help to make executive report from some dimensions mentioned in data warehouse. Sales data will pass through some processes: Extract, Transform, and Load (ETL) in order to prepare the data warehouse. This process is preprocessing data before dimensional model is built. In this research multi-dimensional modelling by taking data from 3 stores ranging from 1 February 2014 to 31 January 2015. By implementing sales executive dashboard, it helps to monitor and analyze sales condition. Dashboard shows graphic which ease user, especially sales manager and owner to learn current and updated sales condition based on dimensions: time, outlet / store, and product. Report gives detail information and multidimensionalhelps to analyze data from different perspective. Index Terms—Dashboard, Multi Dimentional Model, ETL, Executive Reporting REFERENCES[1] W. Eckerson, Performance Dashboard: Measuring,Monitoring, and Managing Your Business, New Jersey: JohnWiley & Sons, 2011. [2] O. Romero and A. Abello, "A Survey of MultidimensionalModelling Methodologies," International Journal of Data Warehousing and Mining, vol. 5, no. 2, pp. 1-23, 2009. [3] R. Kimball and J. Caserta, The Data Warehouse ETL Toolkit:Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data, Indianapolis: Wiley Publishing, Inc., 2004. [4] G. Dhillon and J. Backhouse, "Information System Security Management in the New Millenium," Communications of the ACM, vol. 43, no. 7, pp. 125-128, 2000. [5] C. Ballard, D. M. Farrell, A. Gupta, C. Mazuela and S. Vohnik, Dimensional Modelling: In a Business Intelligence Environment, IBM Redbooks, 2006. [6] E. Fernández-Medina, J. Trujillo and M. Piattini, "Modeldriven multidimensional modeling of secure datawarehouses," European Journal of Information Systems, vol. 16, no. 4, pp. 374-389, 2007. [7] E. Johnson and J. Jones, Building ETL Processes for Business Intelligence Solutions Built on Microsoft SQL Server, CA ERwin, 2007. [8] J. Mylopoulos, L. Liu and M. T. Owen, "Database Design," inEnsyclopedia of Database System, United States, Springer,2009, pp. 708 - 710. [9] K. R. Gadda and S. Dey, "Business Intelligence for PublicSector Banks in India: A Case study. Design, Development,and Deployment," Journal of Finance, Accounting and Management, vol. 5, no. 2, pp. 37-58, 2014. [10] D. J. Power, "DSS Resources," 6 June 2007. [Online]. Available: http://dssresources.com/. [Accessed 29 May 2017]. [11] D. Hedgebeth, "Data-driven decision making for the enterprise: an overview of business intelligence applications," The Journal of Information and Knowledge Management System, vol. 37, no. 4, pp. 414-420, 2007. [12] S. Williams and N. Williams, The Profit Impact of Business Intelligence, San Fransisco: Elsevier, 2007. [13] Imelda, "Business Intelligence," in Majalah Ilmiah Unikom, Bandung, UNIKOM, 2013, pp. 111-112.