Data mining: an exploratory overview.
- Authors: Ferreira, Rian Johan
- Date: 2008-04-22T06:17:29Z
- Subjects: business intelligence , data mining
- Type: Thesis
- Identifier: uj:8535 , http://hdl.handle.net/10210/268
- Description: Managers the world over complain that they are overwhelmed by the amount of data available to them, but that they are unable to make any sense of this data. The changing business environment and the fact that customers are becoming more and more demanding highlight the need for organisations to be able to adapt faster and more effectively to those changes. Data mining developed as a direct result of the natural evolution of information technology. The increased organisational use of computer based systems has resulted in the accumulation of vast amounts of data, and the need for decision makers to have efficient access to knowledge, and not only data, has resulted in more and more organisations adopting the use of data mining. The promise of data mining is to return the focus of large, impersonal organisations to serving their customers better and to providing more efficient business processes. Indeed, for some organisations data mining offers the potential for gaining a competitive advantage, but for others it has become a matter of survival. The literature is filled with examples of the successful application of data mining, not only to specific business functions, but also in specific industries. Undoubtedly, certain industries, such as those dealing with huge amounts of data, and those exposed to many diverse customers, stand to benefit more from data mining than others. iii The benefits, associated with data mining, for organisations, individuals and society as a whole, far exceed its drawbacks, but the biggest issue facing organisations that want to employ data mining, is its cost. The other drawbacks of data mining relate to the threat that it poses to privacy, and any data mining effort must not only be done within the framework of the relevant laws, but must also be done in an ethical manner. Although data mining is probably beyond the financial ability of most organisations, its main principle, the fact that there might be value in organisational data, should not be forgotten. Organisations must endeavour to treat their data with the same respect it has for all its other corporate assets. , Mr. C. Scheepers
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An assessment of the level of maturity of the competitive intelligence function within a South African retail bank.
- Authors: Heppes, David Wayne
- Date: 2008-04-22T06:16:35Z
- Subjects: South Africa , competition , banks and banking , business intelligence
- Type: Thesis
- Identifier: uj:8447 , http://hdl.handle.net/10210/260
- Description: This research is a study of the level of maturity of the Competitive Intelligence (CI) function within a South African retail bank. In particular it focussed on the level of maturity of the CI function as evidenced in the various elements of its CI function, namely the key information needs of CI users, CI deliverables and capabilities, analytical products, relationship with management, sources of information, personnel their skills and training as well as the period of time the CI function has been operational. The results indicated that the CI function as a whole was at a Mid-Level of maturity, with the underlying elements of the CI functions surveyed and the literature review being supportive of this finding. , Prof. A.S.A. du Toit
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