The impacts of implementing a data warehouse in the banking industry
Data warehousing in the financial sector
In the modern banking and financial sector, there is keener and stronger competition and many enterprises are much more eager to get immediate and accurate information to make better and faster decisions. Furthermore, with many banks fighting to capture new customers and the rapidly growing need for larger amounts and more specific information, traditional databases are incapable of effectively handling the demands of increasing online information retrieval, access, update, and maintenance (Hsin-Ginn Hwang et al). This inability greatly impacts businesses in a way that the management level cannot utilise internal data efficiently and effectively to assist reliable decision-making in a timely manner. As a result, it is such a critical issue for every business to seek for ways and/or means to access, store, maintain, and utilise the massive data efficiently. The method that best fulfils the needs of the business is a data warehouse.
A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process (Inmon). It also acts as a specially prepared repository of data created to support decision making. Data is extracted from source systems, cleaned, scrubbed, transformed, and placed in data stores (Gray and Watson 1998). Data warehousing is near the top, if not at the top, of most companies’ strategic IT initiatives. These repositories of data have great potential for providing insight into client behaviour in client-to-business e-commerce, implementing customer relationship management strategies, and supporting comprehensive performance measurement systems.
Within the financial and banking industry, it is becoming evident that corporations are realising the importance of a customer-orientated strategy that places the customers at the centre of all aspects of the company’s operations (Cooper 2000). It is apparent in First American Corporation (FAC) that a data warehouse was introduced to address various issues that caused the company to lose $60 million in 1 year. Many of the issues that are addressed in FAC are interchangeable with other companies in the financial industry. These issues focus on identifying client behaviour, client buying preferences and client value positions which enables the bank to establish the most profitable customers.
An assessment of the impacts of the implementation of a data warehouse
Management support is consistently identified as one of the most important factors for data warehousing success. It motivates people in the organisation to support the data warehousing initiative and the organisational changes that inevitably accompany it (Curtis and Joshi 1998). Management support can overcome political resistance and encourage participation throughout the organisation, and it has been found to be important to the success of many kinds of IT implementations, such as decision support systems (Wixom, 2001). Therefore it is important that prior to and during the introduction of a data warehouse, that there is absolute management support. Users tend to conform to the expectations of management, and they are more likely to accept a system that they perceive to be backed by the management of their organisation (Karahanna et al. 1999). It is also important that management create a culture within the business that focuses on all employees working in conjunction to ensure that the data warehouse is successful. If employees are felt to be left in the dark, they are likely to become unmotivated and stop working effectively, which in turn will cause the data warehouse to fail.
With the implementation of a data warehouse, which is a form of a knowledge management system, there are three main considerations that managers must take into account (Alavi and...
References: 2. Cooper, B. (2000) Data Warehousing Supports Corporate Strategy at First American Corporation MIS Quarterly, Vol 24 No. 4, pp 547-567.
3. Curtis, M.B., Joshi, K
4. Goodhue D. L., Wybo M.D., Kirsch, L. J. (1992) The Impact of data integration on the costs and benefits of information systems, MIS Quarterly, Vol. 16, No. 3. pp. 293-311.
5. Gray, P. and Watson, H.J. (1998) Decision Support in the Data Warehouse. Upper Saddle River, NJ; Prentice-Hall PTR.
6. Grover, V
7. Hsin-Ginn Hwang et al. (2004) Critical factors influencing the adoption of data warehouse technology: a study of the banking industry in Taiwan, Decision Support Systems 37, 1 – 21.
9. Kettunen, Juha; Kantola, Ismo (20050 Campus-Wide information systems, Volume 22, Number 5, pp. 263-274.
10. Markus, M. L. (1983) Power, politics, and MIS implementation, Communications of the ACM(26:6), pp. 430-444.
11. Wells, N., Wolfers, J. Finance With A Personalised Touch, Communications of the ACM , Vol. 43, No. 8, 2000, pp 31-34.
12. Wixom, B. H., Watson, H. J. (2001) An Empirical Investigation of the Factors Affecting Data Warehousing Success, MIS Quarterly, Vol. 25, No. 1., pp. 17-41.
Please join StudyMode to read the full document