SUCCESS FACTORS IN DATA WAREHOUSE PROJECTS Essay

SUCCESS FACTORS IN DATA WAREHOUSE PROJECTS - Essay Example Why organizations need to bring data together from different working systems? Obviously, the answer is, to be more beneficial, to be more competitive, or to grow by adding value for customers. This can be achieved by mounting the pace and flexibility of decision making, developing business processes effectively, or gaining a clearer idea of customer activities. The data warehouse is a huge collection of the past and current business data that analyze the old business data for offering special discounts and trend assessment in the past business. These systems also facilitate decision makers to retrieve data as many times as they need without disturbing the performance of the core working systems. A data warehouse merges data that are scattered all over the different working systems and makes them readily accessible for decision support applications (Laudon & Laudon, 1999, p. 247; Inmon, 2002, p. 3; Hoffer, Prescott, & McFadden, 2007, p. 47). There are many factors that play a signific ant role in the implementation of a data warehouse. This essay presents a detailed analysis of the critical success factors in the implementation of data warehouse projects. Data Warehouse: An overview A data warehouse is a large size subject-oriented database that is designed and implemented with organization-wide access in mind. Additionally, a data warehouse collects and process a mountain of data from a number of sources and the basic purpose of this data collection and processing is to allow its users to be familiar with the data and information they want for decision making and get access to that information by making use of easy to use applications and tools. In addition, data warehouse encompasses a wide variety of tools and technologies such as multidimensional and relational databases, graphical user interfaces, client/server architecture and many more. In the context of a data warehouse system, all these components work with the purpose of combining raw data and facts fro m a variety of sources into a particular and reliable warehouse that provides an excellent support for decision making and analysis inside a particular domain of the business. In this scenario, the majority of large size business organizations develop data warehouse systems as a key element of their main information systems environment (Alshboul, 2012; Swalker, 2011). Data Warehouse Projects A few years ago, it was a serious challenge for the business organizations to actually make use of the covered data and information and facts stored in the functional systems for management and decision tasks. In this scenario, data management is seen in the sense of data as a significant asset belonging to the entire business organization for management and decision tasks, and not only as the belongings of specific tools and applications, personnel or business areas. Basically, this data collected from a variety of sources is supplied to a managerial part, which is responsible for transforming collected data into understandable and useful information for instance high-class subject orientated information will be accessible just in due course. In view of the fact that data can play a significant role in supporting functioning tasks very competently, hence it does not repeatedly make available information that can transform knowledge and improve the efficiency of business processes efficiency. In the past, these operational data were not accessible in a way that end users could straightforwardly recognize and utilize. In this scenario, in the form of a theoretical framework in the direction of contemporary information processing system a data warehouse was developed for a useful and well-organized practice of the