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Published Release Notes

Find release notes for the selected Pega Version and Capability

Browse resolved issues for Platform releases.

This documentation is for non-current versions of Pega Platform. For current release notes, go here.

Encrypt sensitive case data by using a secure default Pega Platform cipher and AWS KMS keys

Valid from Pega Version 7.3.1

You can encrypt sensitive data within your application without having to write custom cipher classes. You can configure encryption on the Data Encryption landing page by using your own keys managed in your private Amazon Web Services Key Management Service (AWS KMS) instance. Pega® Platform encryption uses keys that are stored in AWS KMS to support both time-based and on-demand key rotation. Technical issues can arise in some cases, for example, if a key is deleted from AWS KMS.

For more information, see Potential problems with keystores when using AWS KMS, Configuring a Platform cipher, Types of ciphers.

DateTime control enhancements

Valid from Pega Version 7.3.1

The DateTime (calendar) control has been updated. You can now show week numbers on the calendar, disable weekends so that users cannot select them as working days, show minutes in intervals, and use spinners to facilitate navigating between months and years. These design-time options make it easier for users to select valid dates and times in your applications.

For more information, see Adding and configuring a DateTime control.

Decision Data Store and HDFS data set types become resumable

Valid from Pega Version 7.3.1

Decision Data Store (DDS) and HDFS data set have been enhanced to be resumable. As a result, data flow runs that reference Decision Data Store or HDFS data sets as their primary data source are now resumable. You can pause and resume such data flow runs.

For more information, see the Resumability of data flow runs section in Data flow run updates.

Conditional paths added to case life cycle

Valid from Pega Version 7.3.1

You can now add a conditional path to a process in the life cycle of a case. By defining the decisions that cause a process to follow different paths, you can create cases that support more than one outcome.

For more information about conditional paths, see Conditional paths in a case life cycle.

Receive and reply to push notifications for Pulse messages

Valid from Pega Version 7.3.1

You can now receive push notifications on your mobile device when another user references you in a Pulse message or likes your messages in a Pulse conversation. You can both receive and reply to the push notifications that you get when another user posts on your profile, adds messages to a Pulse conversation in which you are involved, or posts comments on a case that you are following. To receive push notifications, select mobile push as a notification channel when you configure your notification preferences.

For information about Pulse enhancements, see Pulse enhancements for social collaboration.

Integrate the intelligent interaction activity for text analytics into your application

Valid from Pega Version 7.3.1

Employ text analytics and machine-learning capabilities in multichannel applications by integrating the pyRunInteraction activity for content parsing and analysis. By calling this activity, you can automatically analyze any incoming text data, such as instant messages, posts, emails, and so on, to detect sentiments, categories, entities, or intents that can help you with automatic case creation and routing. For example, you can use this activity to populate case properties based on detected entities such as customer name, email address, and account number.

For more information, see Intelligent interaction in text analytics.

Update text analysis models during every interaction

Valid from Pega Version 7.3.1

While interacting with your customers through text-based communication channels (such as a Facebook chatbot or email), you can use an activity to provide feedback to a text analysis model by manually assessing whether the entities, categories, intents, and sentiments in the analyzed text were assigned to the expected class. By using this feedback input as training data, you can ensure that the accuracy of your text analytics models continuously improves.

For more information, see Feedback loop for text analysis.

Build predictive models with the genetic algorithm

Valid from Pega Version 7.3.1

A genetic algorithm solves optimization problems by creating a generation of possible solutions to the problem. In Pega® Platform you can utilize the functionality of genetic algorithms by using the genetic algorithm model in the Analytics Center portal. With this type of predictive model, you can create highly predictive, non-linear models by selecting the best performing model from the last generation.

For more information, see Creating models and Creating a genetic algorithm model.

Use of the @java function in expressions is deprecated

Valid from Pega Version 7.3.1

Use of the @java function in expressions is deprecated. Use a utility function or other product feature instead.

For more information about expressions, see Building expressions with the Expression Builder.

Change passwords from Pega Mobile Client

Valid from Pega Version 7.3.1

You can now change your Pega® Platform password from a mobile device. After your password expires and you try to log in to a custom mobile app, Pega Mobile Client lets you define a new password and verifies it against active password policies.

For more information, see Enabling security policies.

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