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Support for Query/Reporting, OLAP, and Data Mining

Statistical Tools

In addition to query and reporting, and OLAP, statistical tools are used to draw conclusions from representative samples taken from large amounts of data.

Statistical tools are useful for finding patterns and correlations in average amounts of data, but they fall short when the amount of data begins to overwhelm the tool.

For example, traditional statistical techniques struggle when you deal with 25 input variables and tens of thousands of records. When statistical tools cannot analyze all the data, they force data analysts to use representative samples of the data and eliminate input variables from the analysis. This results in discarding information that might be useful.

Query and reporting, OLAP, and statistical tools are good at allowing the user to drill down and understand what has happened in the past.

In contrast, data mining is useful in predicting future behavior.

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