Information Technology & Strategic Management

Information technology (IT) has been and continues to be applied in a wide range of economic activities. One of the latest and potentially most significant advances in IT in relation to organizational performance is the development of innovations in information technology that hold the potential to influence the structure of strategic management systems in organizations (Cohen, 1995).

Information is critical to organizational performance in the contemporary knowledge-based economy. As a consequence, information systems have become a primary organizational resource. The management of information systems in contemporary organizations is in a period of transformation (Balaban & Rothschild, 2002).

An effective strategy is not necessarily one that promises maximum efficiency or least total cost, but rather one that fits the needs of the organization and strives for consistency between the organizationÆs capabilities and the competitive advantage being sought by the organization. The successful application of strategy in the contemporary global environment requires an organization to have an effective strategic management process. In turn, an effective strategic management process increasingly depends on the effective application of advances in information technology (Litman & Lohr

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ternal databases provide the core of a data warehouse for the organization. When developing a data warehouse, however, an organization may find that it is necessary to obtain supplementary data, such as demographic or socioeconomic data, and apply it to in-house or primary data sources (Myburgh, 2002). A data warehouse schema is an overall logical, or conceptual, view of the relationships among the data. It is necessary to design sub-schemas for each of the user application programs that will access the data warehouse. A sub-schema is a subset or transformation of the logical view of the data warehouse schema that is required by a specific application program (Wilken, 1998). Data mining, therefore, refers to the process of deriving knowledge from data stored in databases through the identification of patterns from past behaviors that exist within the data stored in the database. Among the more prevalent approaches to the discovery of such patterns are decision tree induction and association rule discovery (Wilken, 1998). An important issue in data mining is assuring that the expression of discovery tasks and discovered knowledge to be as close as possible to natural languages. This approach satisfies user needs with ôtractabi
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Some common words found in the essay are:
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Approximate Word count = 9202
Approximate Pages = 37 (250 words per page)

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