User Requirement Analysis in Data Warehouse Design: A Review <s> Discussion <s> Information requirements analysis for data warehouse systems differs significantly from requirements analysis for conventional information systems. Based on interviews with project managers and information systems managers, requirements for a methodological support of information requirements analysis for data warehouse systems are derived. Existing approaches are reviewed with regard to these requirements. Using the method engineering approach, a comprehensive methodology that supports the entire process of determining information requirements of data warehouse users, matching information requirements with actual information supply, evaluating and homogenizing resulting information requirements, establishing priorities for unsatisfied information requirements, and formally specifying the results as a basis for subsequent phases of the data warehouse development (sub)project has been proposed. The most important sources for methodology components were four in-depth case studies of information requirements analysis practices observed in data warehousing development projects of large organizations. In this paper, these case studies are presented and the resulting consolidated methodology is summarized. While an application of the proposed methodology in its entirety is still outstanding, its components have been successfully applied in actual data warehouse development projects. <s> BIB001 </s> User Requirement Analysis in Data Warehouse Design: A Review <s> Discussion <s> In this paper we address the issue of failure of data warehousing projects due to an inadequate requirement collection and definition process. We describe a framework that can help accomplish the objective of developing a business driven, actionable set of requirements. The framework consists of a series of steps that facilitate an effective data warehouse requirement collection and definition phase. The paper also addresses the difficult yet common issue of end-users' limited availability during the requirement collection process and proposes an approach that can serve to alleviate this problem. <s> BIB002
It is paramount to choose the right user requirement approach that might be suitable to organization environment. Recognizing the strengths and weaknesses of each approach could assist the process of selecting suitable user requirement analysis that might contribute to successful data warehouse project. There are few advantages in applying data driven approach. First and foremost it could simplify ETL design  , BIB002 ,  . Since the requirements selection are based on data available in data source, it is easy to construct data warehouse schema BIB001 and at the same time ensure data availability. Data source schema is normally stable and does not change repeatedly. This will establish high stability in multidimensional schema  compare with requirements based on end user needs. However there are few weaknesses of data driven approach. This approach is high risk of wasting resources to handle unneeded information structure [4] , BIB001 . With abundant of information from data source, it is almost impossible to extract relevant requirements  .This will diminish end user motivation to participate in design process especially when they need to work with large data model [4] . In addition, it is possible that the result of multidimensional schema did not fit user requirements  due to lack of end user involvement. The user driven approach gives priority to user requirements BIB002 and encourages high end user participation during DW design process BIB001 . With this approach, DW is tailored exactly to end user's need  and it is highly appreciated by business user  . It minimizes risk of wasting resource BIB001 as a result of mapping requirements with certain data available in data source. On the other hand, this approach requires large effort in designing ETL  , BIB002 and difficult in mapping user needs onto available data source  . Failure in mapping user needs will lead to user disappointments. In addition, it is a risk that end user normally not capable to specify requirements that could assist in achieving business goals because they don't have sufficient knowledge or understanding of whole business process and organizational visions. However, to ensure successfulness of eliciting and integrating user requirements, great effort from project manager with good moderation and leadership skill is required. Alternatively, it is suitable to apply goal driven approach that will focus on goals and strategies of the company for an efficient decision making. This will maximize probability of correct identification of relevant indicator. However, it fully depends on the willingness of top management to involve in DW design process. Table 1 reports comparison between mixed-driven approaches to organization environment, technical team and analysis output that involve in DW project. Organization environment considered in this study are divided into level of involvement among top management and end user to provide user requirements. This is important characteristic to be considered in choosing appropriate approach because it will be the main input to DW project. Another consideration is about time frame of project. Most of DW projects require long term planning. However, it depends on the organization requirements and failure to deliver project on time could draw millions of dollars. Second important consideration is the technical team skill. They should be able to deal with diagram notation and modelling technique complexity. Finally is the output of approach that being classify into DW schema quality and ability to fulfil business goal. The main consideration in choosing suitable approach is the characteristic of organization itself. For example if the organization itself gets high commitment from top management but not from end user, it is suitable to choose GRAnD approach that could lead to high quality of data warehouse schema and high probability in fulfilling business goals.