Using Built-In Advanced Analytics

Econometrics is used to analyze quantitative and qualitative economic relations by means of mathematical and statistical methods and models. Econometrics is used to forecast economic processes.

NOTE. Working with econometrics is available if report data area is based on a time series database.

Econometrics methods can be applied to data by using the following Foresight  Analytics Platform tools: Time Series Analysis and Modeling and Forecasting.

To apply econometrics methods:

1. Select a data range in report data area.

2. Open the Advanced Analytics ribbon tab.

3. In the Econometrics group click the button corresponding to Foresight Analytics Platform:

• Time Series Analysis. A workbook opens that contains selected data and uses the same time series database as report data area does, as a data source.

• Modeling and Forecasting. A modeling problem opens, which calculates the chain of models based on the selected data.

Perform econometric data analysis by using functionality of the selected tool.

Validation is used to check time series data for correspondence with the set conditions and constraints.

NOTE. Working with data validation is available if report data area is based on a time series database.

To validate data:

1. Create a validation rule or make sure if the required rule already exists in the time series database, which is used as a data source on the report data area.

2. Select a data range in report data area.

3. Open the Advanced Analytics ribbon tab.

4. Click the Validation Rules button in the Data Validation group.

5. The list opens, in which select the required validation rule.

After executing a series of actions for the selected data range, validation is executed.

On working with exceptions, the user can execute the following operations:

• Navigate by exceptions.

• Show or hide validation legend.

• Clear validation results.

For detailed description of working with data validation see the Data Validation section.

Data mining is used to reveal hidden facts and relations in large data arrays. Obtained data may be used to make decisions in various life spheres.

To execute data mining:

1. Select a data range in report data area.

2. Open the Advanced Analytics ribbon tab.

3. Click the button, corresponding to the analysis method in the Data Mining group.

• Clustering. It divides data into the set number of groups by means of the selected method.

• Exception search. It determines the degree of exceptionality for each attribute of each object by judging the general collection of data. The obtained characteristics can be used to rank objects by the degree of their exceptionality.

• Pattern substitution. It uses the current classification to fill in missing values of the explained attribute on the values of explanatory attributes.

• Key factors. It estimates the degree of influencing of each factor on the dependent variable and reveals most relevant factors.

• Association analysis. It determines most frequent joint sets of elements by means of the analysis of the set of repeated transactions.

• Forecasting. It enables the user to apply the specified forecasting method to continue the specified time series using information on its frequency.

The data mining wizard opens to perform the analysis.