Published Release Notes

Data schema error on z/OS split schema upgrades from versions before Pega 7.1.8

When upgrading to a split schema on Pega 7.x with IBM DB2 for z/OS, you see an error during the data schema upgrade when the system tries to drop the PRPC_Updatescache procedure. Because triggers on rules tables use PRPC_Updatescache, you must use the ZOSDisableTriggerScripts to disable these triggers before you update the data schema.

1. Follow the instructions in the Pega 7 Platform Upgrade Guide to upgrade the rules schema, but stop immediately before you upgrade the data schema with the upgrade.bat or upgrade.sh script. The Pega 7 Platform Upgrade Guide is on the Support > Deployment Guides page.
2. Copy the contents of the <distribution>\ResourceKit\ZOSDisableTriggerScripts directory into the <distribution>\scripts\ directory.
3. Run fixZosTriggers.bat or fixZosTriggers.sh with the following arguments:
   --action preupgrade
--dataschema <data schema name>
   --oldrulesschema <old rules schema name. If you are upgrading from a single-schema system, this is the data schema name.>
   --newrulesschema <new rules schema name>
   --automaticddl <Optional. Set to true to automatically apply the disable trigger SQL scripts.>

   For example:
   fixZosTriggers --action preupgrade --dataschema pegadata --oldrulesschema pegarules --newrulesschema newrules --automaticddl false

4. If you did not set --automaticddl to true in the previous step, run the <distribution>\schema/disable.sql script to manually disable the trigger SQL scripts.
5. Run the data schema upgrade as described in the Pega 7 Platform Upgrade Guide.

Specify the scope for rolling back rules and data to a restore point

Create restore points to save the state of all rules and data in your system at a significant point in time, for example, before you import an application. Roll back to that restore point to return the system to that state. Now, you can filter which rule and data instances are returned to their previous state:

• System: Roll back every rule and data instance that has a history record.
• User: Roll back rule and data instances modified by a specific user. If any rule was changed by more than one user, you will see an error message and must use the system rollback.
• Application: Roll back rule and data instances in a specific application.

For more information, see Using restore points to enable error recovery.

Connect to Amazon SageMaker models in Prediction Studio

Make the most of your custom Amazon SageMaker models in Pega Platform™ by connecting to the models in Prediction Studio. You can then run the Amazon SageMaker models as part of your decision strategies.

For more information, see Enrich your decisioning strategies with H2O and Amazon SageMaker predictive models (8.4).

Import H2O models to Prediction Studio

Make the most of your custom H2O models in Pega Platform™ by importing them to Prediction Studio. You can then include the H2O models in your decision strategies.

For more information, see Enrich your decision strategies with H2O and Amazon SageMaker predictive models (8.4).

Support for auditing adaptive model decisions

Pega Platform™ now stores all adaptive model scoring data so that you can identify the source of each decision, such as the exact model version that was used for scoring. With this feature, you can ensure that your application is auditable, transparent, and in compliance with regulatory requirements related to using adaptive models.

For more information, see Configuring the Adaptive Decision Manager service.

Create predictions in Prediction Studio

Predict customer behavior and business events by creating predictions. To create a prediction, you answer a series of questions about what you want to predict. For example, you can create a prediction to determine the likelihood of customer churn.

For more information, see Create predictions in just a few clicks (8.4).

New text analytics APIs for Intelligent Virtual Assistant

Pega Platform™ now provides text analytics APIs that separate Intelligent Virtual Assistant and text analyzers into independent modules. This solution prevents integration issues when you change your text analyzer configuration.

For more information, see Text analytics APIs.

Optimized performance of embedded decision strategies

The performance of embedded strategies has now been optimized so that these strategies take less time and fewer CPU and memory resources to complete. This enhancement increases the performance of cloud and on-premises deployments.

For more information, see About Strategy rules.

New method of aggregating real-time events

Event Strategy now uses the approximate median for calculating aggregations. Approximate median calculation replaces the existing method because it requires fewer system resources for saving or loading the event strategy state. In addition, you can now calculate aggregated values by using a new Landmark window type. The window type captures all values of specific event properties from the start of the data flow that references the event strategy.

For more information, see Adding aggregations in event strategies.

Extended language support in text analytics

Pega Platform™ text analytics now supports 9 more languages. You can build entity and topic detection models to analyze text in the Japanese, Russian, Turkish, Danish, Norwegian, Swedish, Polish, Croatian, and Czech languages. In addition, Pega Platform now includes a default small talk detection model for each of these languages.

For more information, see Language support for NLP and Out-of-the-box text analytics models.