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Published Release Notes

Find release notes for the selected Pega Version and Capability.

Browse resolved issues for Platform releases.

Stakeholder management extended to case followers

Valid from Pega Version 7.4

You can now control which users follow a case. By actively involving the people with relevant skills and roles in your application, you can resolve cases more quickly.

For more information, see Case followers.

Enhanced adaptive model reporting

Valid from Pega Version 7.4

The new Model report replaces the Behavior and the Performance overview reports to improve report usability and provide consistent information. You can export your Model reports into PDF or Excel files to view or share them outside the Pega® Platform. The Model report also includes information on the groups of correlated predictors where the best performing predictor from each group is active in the model and other remain inactive; this information helps you understand why predictors are active or inactive.

For more information, see Generating a model report.

Pulse enhancements

Valid from Pega Version 7.4

The enhanced layout of the Pulse interface provides a better user experience for posting messages, adding attachments, bookmarking content, and so on. You can now post messages in your activity feed, format messages, add inline images and links to messages, reference cases, and view the list of users who like messages. The Pulse email templates have also been improved to display email content in a coherent and structured format.

For more information, see:

Use Kinesis data sets in Pega Decision Management

Valid from Pega Version 7.4

You can create Kinesis data set instances to connect to Amazon Kinesis Data Streams and use this data set in decision management for processing real-time streaming data. Integrating Kinesis data streams into Pega® Platform in the cloud provides a fault-tolerant and scalable solution for processing IT infrastructure log data, application logs, social media, market data feeds, and web clickstream data.

For more information, see Creating a Kinesis data set.

View attachments inline

Valid from Pega Version 7.4

You can now view thumbnails of PDF file and image attachments and icons of video attachments in Pulse, cases, and other areas of the application that allow you to attach files. Thumbnails provide a preview of your attachments inline. You can also play video attachments and expand the thumbnails of PDF file and image attachments to view them in readable formats.

For more information, see Inline preview of attachments.

Store and scale the processing of Stream data records on multiple nodes

Valid from Pega Version 7.4

You can configure the Stream service on Pega® Platform to ingest, route, and deliver high volumes of low-latency data such as web clicks, transactions, sensor data, and customer interaction history. You can store streams of records in a fault-tolerant way and process stream records as they occur. Add or remove Stream nodes to increase or decrease the use of the Stream service and optimize data processing.

For more information, see Stream service overview.

Decisioning services now use default node classification

Valid from Pega Version 7.4

Decisioning services have been integrated with default node classification on Pega® Platform to provide a unified way of creating and initializing services. As a result of the integration, the Data Flow service has been divided into Batch and Real Time services to better handle different types of data flow runs. You can now specify separate subsets of Data Flow nodes for batch data flow runs and real-time data flow runs to divide the workload between these two subsets.

For more information, see Node classification, Data Flows landing page, and Services landing page.

Train machine learning models for extracting named entities and detecting intents

Valid from Pega Version 7.4

Data scientists can train machine learning-based text extraction and intent detection models by using the Analytics Center. With text extraction, you can train a Conditional Random Fields (CRF) model to detect whether the content contains specified entity types such as person names, company and organization names, locations, dates and times, percentages, and monetary amounts. For intent detection, you can train a maximum entropy model to understand user intentions expressed in written content. With these two new capabilities, you can quickly react to customer queries and comments by taking appropriate action against the information that you extracted.

For more information, see Creating machine learning-based text extraction models and Creating machine learning-based intent analysis models.

Edit icons and titles for messages in the activity feed

Valid from Pega Version 7.4

You can now edit the icons and titles of messages that are displayed in the activity feed for Pulse by customizing the pxFeed Pulse gadget. For example, to inform other users of an application about important Twitter updates that are related to the organization, you can create a message that displays a Twitter icon and a title of Twitter updates.

For more information, see Pulse enhancements for social collaboration.

Activity feed displays application messages

Valid from Pega Version 7.4

The activity feed for Pulse now displays messages within the context of the application of the logged-in user. If a user posts messages within the context of the application, all the users of the application can view the messages in their activity feed. Users can select the filter for application messages to view only these messages. For example, application messages can be used for release announcements.

For more information, see:

All Pega product release notes can be found on their product pages.

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