Requirements Engineering For Data Warehouse (Trinity Journal of Management, IT & Media (TJMITM), 2012)
Our research paper will focus on the effectiveness of a  requirement engineering process on organizational data  warehouses used by the business analysts and managers  for an effective decision making during critical situations.  The global slowdown due to economic recession of 2008- 09 also affected the business climate within India and the  growth rate of the Information Technology Sector. But,  India being a developing economy managed to survive the  economic recession to an extent. This paper focuses on  the important role played by organizational data warehouse systems used for making important decisions  during hard times that help in averting the impact of  recession to a large extent. Recession presented businesses with a dilemma: whether  to cut costs to conserve resources, or to invest in new  products and processes to exploit competitor weakness.  Here comes the need of correct data on which strategic  decisions can be made. Thus the need of an effective  requirement engineering phase is there. The policies laid  down by Indian Govt. caused a total change in the way in  which India does business. There are challenges facing  managers together with hope for more initiative and  creativity, leading to success for industry and for the whole  nation. Building of efficient Data Warehouse and its maintenance  is a costly and time consuming process. To overcome this  problem, we should use such a technique that helps in  exploring and clarifying each requirement in detail which  can be considered while constructing the Data Warehouse  at an early phase. The importance of an effective  requirement engineering phase lies in the fact that if  requirements are properly identified in the beginning, then  the data warehouse would be built on an almost correct  data. Correctly gathered and represented data would help  the business managers to take an apt decision in the face  of uncertainty to optimize the resources available at their  disposal.
Keywords: Engineering; Data Warehouse; Requirement Analysis; Requirement gathering techniques; ETL Process (Data Staging Process)