Database Marketing, Business Intelligence and Knowledge Discovery

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Knowledge Discovery Process Models CRISP-DM model – Evaluation After building one or more models that have high quality from a data analysis perspective, the model is evaluated from business objective perspective. The model is thoroughly evaluated, and review of the steps executed to construct the model is performed. A key objective is to determine if there are important business issues that have not been sufficiently considered. At the end of this phase, a decision on the use of the DM results should be reached. The key sub-steps in this step include: – evaluation of the results – process review, and – determination of the next step. Engineering and Technology Management 24
Knowledge Discovery Process Models CRISP-DM model – Deployment It involves organization and presentation of the discovered knowledge in a way that the customer can use. Depending on the requirements, this can be as simple as generating a report or as complex as implementing a repeatable KDP. This step is further divided into: – planning of the deployment – planning of the monitoring and maintenance – generation of final report, and – review of the process sub-steps. Engineering and Technology Management 25
Page 1 and 2: Database Marketing, Business Intell
Page 3 and 4: Database Marketing Classic databas
Page 5 and 6: BI Components and Architecture Engi
Page 7 and 8: Business Analytics Business anal
Page 9 and 10: Knowledge Discovery The process of
Page 11 and 12: Text Mining The application of da
Page 13 and 14: Data Life Cycle Process Engineering
Page 15 and 16: Knowledge Discovery Process KDP is
Page 17 and 18: Knowledge Discovery Process Models
Page 23: Knowledge Discovery Process Models
Page 35: Comparison of the Knowledge Discove

Database Marketing, Business Intelligence and Knowledge Discovery

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