The Impacts of Implementing a Data Warehouse in the Banking Industry
The impacts of implementing a data warehouse in the banking industry
Data warehousing in the financial sector
Introduction
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
Data warehousing in the financial sector
Introduction
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
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