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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.

Enabling security policies now requires current password

Valid from Pega Version 7.1.3

As part of Pega’s initiative to protect against malicious attacks, the change password dialog has been enhanced.  When Security Policies have been enabled for your system, new users or those with expired passwords will now be prompted for both their existing password as well as their desired new password.

For more details, review the Designer Studio > System > Settings > Security Policies landing page.

Decision Strategy Manager

Valid from Pega Version 7.1.3

Fixes were made that improve the configuration and execution of Batch Decisions. In particular,  the capability to use Structured Data has been enhanced. Some notable improvements have also been made to the UI of Visual Business Director.

  • The structured data input configuration will now work even though there is no data.
  • VBD has been enhanced to work with Version 7.1.
  • The structured data input configuration will now work with nested structures.
  • Association rules from Version 6.3 will now work with 7.1 structured data.

Support for OAuth 2.0 authorization code grant type

Valid from Pega Version 8.1

Pega Platform™ now supports the OAuth 2.0 authorization code grant type, which allows Pega Platform to act as an OAuth 2.0 access token provider for native applications on mobile and other devices. By using the authorization code grant type for mobile clients, you no longer need to implement a variety of standards for various authentication providers. The authorization code grant type also supports the Proof Key for Code Exchange standard (PKCE) for securing public clients.

For more information, see Creating and configuring an OAuth 2.0 client registration.

Use client-based access control to support EU GDPR requirements

Valid from Pega Version 8.1

You can use client-based access control (CBAC) to satisfy the data privacy requirements of the European Union General Data Protection Regulation (GDPR) and similar regulations. By using client-based access control, you can identify the personal data of clients and automatically process requests to view, update, or remove the data in a secure manner. You can also enforce restrictions on the use of this data in application functions.

For more information, see Client-based access control.

Use repositories as sources for File data sets

Valid from Pega Version 8.1

You can configure remote repositories, such as Amazon S3 or JFrog Artifactory, or a local repository, as data sources for File data sets. By referencing an external repository from a File data set, you enable a parallel load from multiple CSV or JSON files, which removes the need for a relational database for transferring data to Pega Platform™ in the cloud.

For more information, see Creating a File data set record for files on repositories and Configuring a remote repository as a source for a File data set.

Define a taxonomy by using the Prediction Studio interface

Valid from Pega Version 8.1

Create a topic hierarchy and define keywords for each topic in Prediction Studio faster and more intuitively than by editing a CSV file. If you have already defined a taxonomy in a CSV file, you can import that file and modify existing topics and keywords by using the Prediction Studio interface.

For more information, see Creating-keyword-based topics for discovering keywords and Tutorial: Configuring a topic detection model for discovering keywords.

Improved performance of decision strategies

Valid from Pega Version 8.1

Strategy rule performance has been improved through the implementation of a new engine. You can perform single and batch test runs to analyze strategy performance, locate and prevent potential issues, and optimize strategy components. Test runs now support data sets and data flows with multiple key properties. The redesigned Test run panel improves the display of information and highlights the most immediately relevant details.

For more information, see Configuring a single case runs and Configuring a batch case runs.

Extract summaries from the analyzed text

Valid from Pega Version 8.1

You can now configure a Text Analyzer rule to extract information-rich blocks of text from the analyzed content and combine them into a comprehensive and coherent summary. By summarizing large documents, such as emails, you can facilitate making business decisions without having to read an entire document. In Text Analyzer rules, you can combine summarization with other types of text analysis, such as topic or entity detection, to extract the full context from a message.

For more information, see Configuring text extraction analysis and Tutorial: Extracting email context with Text Analyzer rules.

Additional adaptive model predictors based on Interaction History

Valid from Pega Version 8.1

Customer interactions are now automatically used in adaptive models to predict future customer decisions. For example, a phone purchase registered in Interaction History allows an adaptive model to predict that a customer is more likely to accept supplementary coverage for a new device. Such interactions, collected in a predefined Interaction History summary, are applied as an additional set of predictors in an adaptive model.

The aggregated Interaction History summary predictors are enabled by default for every adaptive model configuration.

For more information, see Enabling Interaction History predictors for existing adaptive models.

Update text analytics models instantly through an API

Valid from Pega Version 8.1

Use the pxUpdateModels API to automatically retrain text analytics models for which you gathered feedback as a result of the pxCaptureTAFeedback activity. The pxUpdateModels API provides an option to update the model with the latest feedback without having to open Prediction Studio. Instead, you can use the activity from your application, for example, through a button control.

For more information, see Feedback loop for text analytics.

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