Read This Before You Begin

Here are some common terms and basic concepts about the Resource Analytics applications.

Regression is a data mining function that predicts a number. It’s commonly used in prediction and forecasting.

A regression task begins with a data set in which the target values are known. For example, you can develop a regression model that predicts resource usage based on observed data for your middleware and database resources over a period of time. In the model build, a regression algorithm estimates the value of the target as a function of the predictors for each case in the build data. These relationships between predictors and target are summarized in a model, which can then be applied to a different data set in which the target values are unknown. Regression Models are tested by computing various statistics that measure the difference between the predicted values and the expected values.

You can use a linear regression technique if the relationship between the predictors and the target can be approximated with a straight line.

You can use a nonlinear regression technique when the relationship between x and y can’t be approximated with a straight line.

A channel, in the context of a forecasting report based on a given regression model, is simply additional information that may be part of the estimated values. For example, some regression algorithms may also yield confidence levels, which indicate the percentage of confidence that the future values will be within the range of estimated values.

The database storage subsystem controls the physical data files, logs, and other files used by a database. The database storage utilization shows the amount of disk space used by a database or various logical units within the database.

The database interconnect refers to the high-speed, low latency dedicated communication link between the nodes of a database cluster. For example, between the nodes of an Oracle Real Application Clusters (Oracle RAC) environment.