Available in...Big Data Platform
Cloud API Services Platform
Cloud Big Data Platform
Cloud Data Fabric
Cloud Data Management Platform
Data Fabric
Data Management Platform
Data Services Platform
MDM Platform
Real-Time Big Data Platform
You can create several contexts for the same database or file connection and
select specific context parameters with which you want to execute an analysis on the
database or the file connection.
For example, there might be various testing stages you want to perform and validate
before an analysis is ready to go for production use.
Before you begin
You have selected the
Profiling
perspective.
Procedure
-
Follow the procedures outlined in Exporting a connection as a context.
-
In the last step in the Create/Reuse a context group
wizard, click the Configure Contexts... icon.
-
In the Configure Contexts dialog box, click
New....
-
Enter a name for the new context, and click OK to
close the dialog box.
The defined context for the current connection are listed in dialog
box.
-
If required, click New... again and proceed as above to
create as many contexts as needed.
-
Click OK to close the dialog box and then
Finish to close the Create/Reuse a context
group wizard.
In the Database Connection wizard, all connection
settings are set as context and are read-only.
In the file connection wizard, all connection settings are set as context and
are read-only.
-
Click Finish to close the wizard.
The Choose context dialog box is displayed.
-
If required, change the context for the current database or
file connection, and click OK to
close the dialog box.
A message is displayed prompting you to propagate the
modifications to all the Jobs and analyses that use the
connection, if any.
-
Click Yes to confirm the operation and close the message
and the dialog box.
Results
The selected connection is exported as a context and listed as a context item under
the Contexts node in the
Integration
perspective.
For detailed information on centralizing the contexts and variables to be used in
data integration Jobs or data quality analyses, see Centralizing database metadata.