7 what is data mining and how does it differ from

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7. What is data mining, and how does it differ from traditional decision support tools? - Data mining describes a new breed of specialized decision support tools that automate data analysis. - Data-mining tools are based on algorithms that form the building blocks for artificial intelligence, neural networks, inductive rules and predicate logic. - Differs from traditional DSS tools proactive. - The data-mining tools will automatically search the data for anomalies and possible relationships - Thereby identifying problems that have not yet been identified by the end user. 8. Discuss the different phases in the data mining process. - Data mining is subject to 4 phases: 1) Data preparation phase the main data sets to be used by the data-mining operation are identified and cleansed from any data impurities 2) Data analysis and classification phase to study the data to identify common data characteristics or patterns. During this phase the data mining tools applies specific algorithms to find: - Data groupings, classifications, clusters or sequences - Data dependencies, links or relationships - Data patterns, trends and deviations. 3) Knowledge acquisition phase uses the results of the data analysis and classification phase. selects the appropriate modelling or knowledge acquisition algorithms. 4) Prognosis phase the data mining findings are used to predict future behaviour and forecast business outcomes.
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