Data Mining Techniques
- Topics:
- Analysis,
- Business Intelligence,
- Strategic Analysis
- Tags:
- Business Intelligence,
- StatSoft,
- Software,
- Productivity,
- Marketing Research,
- Marketing,
- Enterprise Software,
- Databases,
- Data Visualization,
- Data Mining,
- ...
- Source:
- StatSoft
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Overview: Data mining is the process of exploring large amounts of data in search of important patterns, which can then be analyzed statistically to produce useful information for managers and other decision makers. Examples of useful statistical results include performance metrics, risk measures, and all types of forecasts. This article explains basic data mining and analysis techniques, and offers useful links for further exploration. Some of the data mining techniques covered here include online analytical processing (OLAP), exploratory data analysis (EDA), hypothesis testing, and data visualization methodologies. The article frames these techniques within the three basic stages of statistical model-building: data exploration, model building, and model validation.
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Format: HTML | Date: Jan 2000
