Building an Effective Data Warehouse

This case study provides insight into how a data warehouse was built for a firm in the financial sector using its existing Microsoft technology. It touches on the current form of "static reports" currently used within the company, which we have identified as problematic. This case study showcases a step-by-step method of how this DW is built. After reading, you should understand the theory and practical application of the DW approach. How would you apply a similar framework to a large department store chain's supply chain?

Abstract

This article presents the implementation process of a Data Warehouse and a multidimensional analysis of business data for a holding company in the financial sector. The goal is to create a business intelligence system that, in a simple, quick but also versatile way, allows the access to updated, aggregated, real and/or projected information, regarding bank account balances. The established system extracts and processes the operational database information which supports cash management information by using Integration Services and Analysis Services tools from Microsoft SQL Server. The end-user interface is a pivot table, properly arranged to explore the information available by the produced cube. The results have shown that the adoption of online analytical processing cubes offers better performance and provides a more automated and robust process to analyze current and provisional aggregated financial data balances compared to the current process based on static reports built from transactional databases.

Source: José Ferreira, Fernando Almeida, and José Monteiro, http://pubs.sciepub.com/acis/3/1/4/
Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 License.