| Home | Data mining is the process of finding relevant information by sorting
through large amounts of data. It is used by companies in relation to enterprise
resource planning to help make decisions based on patterns and forecasts
generated by the collected data. Business analysts were able to extract
useful information from
recorded data, but since the
data has grown in size, a computer based approach is used by an
automatic data analysis using more complex and sophisticated tools
instead of a hands-on data analysis. Data mining is applying computer based methodology to the data. Data mining is more than a simple data analysis because it identifies trends in the data such as key attributes of business processes and target opportunities, but the results may be false positives. Data mining is used for the processes of knowledge discovery and prediction or forecasting. Knowledge discovery provides explicit information that is readable and easy to understand for users. Predictive modeling or forecasting includes predictions of future events that may be transparent and readable in some approaches, but not others such as neural networks. Neural networks and other data mining systems involve prediction and pattern recognition and not knowledge discovery. Data mining relies on real world data, but may have unknown interrelations. There are different types of algorithms to build a data mining model. It's critical to choose the right algorithm for the business task. Different algorithms can be used for the same business task, but may have different results. The types of algorithms are classification, regression, segmentation, association, and sequence. Classification predicts one or more discrete variables based on other attributes in the dataset. Regression predicts one or more continuous variables (ex. profit or loss) based on other attributes in the dataset. Segmentation divides data with similar properties into groups or clusters. Association finds correlations between different attributes in a dataset. Sequence analysis summarizes frequent sequences in data (ex. Web path flow). |
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Home | Overview | History | Microsoft Excel vs. Access | Database Management | Relational Database | Database Administration | Data Security | Data Mining | Metadata | Links