In the example below, you want to create nominal correlation analysis to compute the minimal and maximal birth dates for each listed country in the selected nominal column. Two columns are used for the analysis: birthdate and country.
The nominal correlation analysis is possible only on database columns for the time being. You can not use this analysis on file connections.
Prerequisite(s): At least one database connection is set in the Profiling perspective of the studio. For further information, see Connecting to a database.
Defining the analysis
In the DQ Repository tree view, expand the Data Profiling folder.
Right-click the Analyses folder and select New Analysis.
The [Create New Analysis] wizard opens.
Start typing nominal in the filter field, select Nominal Correlation Analysis and then click Next.
In the Name field, enter a name for the current analysis.
Avoid using special characters in the item names including:
"~", "!", "`", "#", "^", "&", "*", "\\", "/", "?", ":", ";", "\"", ".", "(", ")", "'", "¥", "'", """, "«", "»", "<", ">".
These characters are all replaced with "_" in the file system and you may end up creating duplicate items.
Set the analysis metadata (purpose, description and author name) in the corresponding fields and then click Finish.
A folder for the newly created analysis is listed under Analysis in the DQ Repository tree view, and the analysis editor opens on the analysis metadata.
Selecting the columns you want to analyze
In the analysis editor and from the Connection list, select the database connection on which to run the analysis.
The nominal correlation analysis is possible only on database columns for the time being. You can change your database connection by selecting another connection from the Connection list. If the analyzed columns do not exist in the new database connection you want to set, you receive a warning message that enables you to continue or cancel the operation.
Click Select columns to analyze to open the [Column Selection] dialog box and select the columns you want to analyze, or drag them directly from the DQ Repository tree view.
Please notice that if you select too many columns, the analysis result chart will be very difficult to read.
You can right-click any of the listed columns in the Analyzed Columns view and select Show in DQ Repository viewto locate the selected column under the corresponding connection in the tree view.
If required, click in the Indicators view to open a dialog box where you can set thresholds for each indicator.
The indicators representing the simple statistics are by-default attached to this type of analysis.
In the Data Filter view, enter an SQL WHERE clause to filter the data on which to run the analysis, if required.
In the Analysis Parameter view and in the Number of connections per analysis field, set the number of concurrent connections allowed per analysis to the selected database connection, if required.
You can set this number according to the database available resources, that is the number of concurrent connections each database can support.
If you have defined context variables in the analysis editor:
use the Data Filter and Analysis Parameter views to set/select context variables to filter data and to decide the number of concurrent connections per analysis respectively.
In the Context Group Settings view, select from the list the context environment you want to use to run the analysis.
For further information about contexts and variables, see Using context variables in analyses.
Save the analysis and press F6 to execute it.
The graphical result is displayed in the Graphics panel to the right of the editor.
In the above chart, each value in the country and marital-status columns is represented by a node that has a given color. Nominal correlation analysis is carried out to see the relationship between the number of married or single people and the country they live in. Correlations are represented by lines.
To have a better view of the graphical result of the nominal correlation analysis, right-click the graphic in the Graphics panel and select Show in full screen. For more information on the chart, see Accessing the detailed view of the analysis results.