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Published Release Notes

Find release notes for the selected Pega Version and Capability

Browse resolved issues for Platform releases.

Predictive models can drive predictions

Valid from Pega Version 8.6

You can use predictive models as the basis of your predictions. As a data scientist, you can now replace a model in a prediction with a PMML, H2O MOJO, or Pega OXL predictive model, as well as a scorecard or field, and then approve the update for deployment to a production environment. You can respond to a Prediction Studio notification that an active model does not generate enough lift and decide to replace the low-performing model with a high-accuracy model. You can also update a prediction on a regular basis, for example, whenever you develop a new churn model in an external environment.

For more information, see Replace models in predictions and migrate changes to production.

Enhancing the performance of your Next-Best-Action strategy with globally optimized strategies

Valid from Pega Version 8.6

Starting in version 8.6, Pega Platform™ combines the versatility of Next-Best-Action Designer with strategy performance enhancements provided by using globally optimized strategies (GOS). Decrease the run time and memory usage of executing the Next-Best-Action strategy in batch or real-time scenarios by using the globally optimized strategies generated by Next Best Action Designer.

GOS is supported by Pega Platform's standard business change management process. GOS rules are automatically included in relevant revision packages.

For more information, see Enhance the performance of your Next-Best-Action strategy with globally optimized strategies (8.6).

Support for picklists with parameterized data pages in App Studio in Cosmos React UI

Valid from Pega Version 8.6

You can now use data pages with parameters to populate a property of the picklist type with filtered results in App Studio. For example, in a survey case type, you can use a parameterized data page to configure cascading drop-down controls in which the values in a secondary drop-down list are based on the value that the user selects in the primary drop-down list. With dynamically-sourced picklists, you get greater flexibility in configuring picklists, and users see more accurate values.

For more information, see link Dropdown control Properties — General tab.

Easier customer record management in Customer Profile Designer (early preview)

Valid from Pega Version 8.6

The new Customer Profile Designer module of Pega Customer Decision Hub™ makes it possible for marketing analysts and strategy designers to define the associated data for each customer context directly in the Pega Customer Decision Hub portal. It is also possible to define more complex associated data structures that use a custom data flow, or define associated data of different types, such as RDBMS and Cassandra, for the same customer context.

Customer Profile Designer is available in Pega Customer Decision Hub 8.6 version as an early preview version. The functionality will be further expanded in future releases.

For more information, see Manage customer records in Customer Profile Designer (8.6).

Kafka data set enhancements

Valid from Pega Version 8.6

The Kafka data set is a high-throughput and low-latency platform for handling real-time data feeds that you can use as input for Pega Platform event strategies.

For better integration of Pega Platform with externally hosted Kafka, the following enhancements are implemented:

  • Support for Kafka message keys and headers - extended values data format (JSON Data Transform, Apache Avro)
  • Custom value processing
  • Configuring topic names by using Application Properties
  • Data-Admin-Kafka enhancements - supporting a wide range of connection properties

For more information, see Improve your Kafka data set with new enhancements.

Real-time event processing

Valid from Pega Version 7.1.9

Real-time event processing is a mechanism that can be used to analyze a high velocity stream of events entering the system and derive conclusions from them. It is possible to define metrics, measurements, and conditions under which subsequent trigger events are generated.

For details, see Real-time event processing.

Text analytics on the Pega 7 Platform

Valid from Pega Version 7.1.9

The Pega 7 Platform offers users the capability to analyze units of text, extract quality information, and translate it into business intelligence. The text analytics functionality aims to determine the positive, negative, and neutral polarities (tone) of subjective sentences. It also provides mechanisms for categorizing units of text and classifying text elements into predefined categories. You can use it to analyze text-based content including news feeds, emails, and postings on social media streams, such as Facebook, Twitter, and YouTube.

For more information, see Introduction to text analytics on the Pega 7 Platform.

Updates to the Data Flow rule

Valid from Pega Version 7.1.9

It is now possible to use report definitions as primary and secondary sources in the Data Flow rule. The data flows that are sourced by a report definition can be distributed on multiple nodes. When using a database table data set as the destination of the data flow, you need to select one of the save options for the data set (insert records or insert and update records).

Updates to the Event Strategy rule

Valid from Pega Version 7.1.9

When you design event strategies, you can use the Filter shape for basic arithmetic and text expressions. You can also specify start conditions for the tumbling and sliding windows.

Updates to the Predictive Model rule form

Valid from Pega Version 7.1.9

The Predictive Model rule form provides the XML schema preview for uploaded PMML models. You can use this preview to view the structure of a model and to correct errors before saving the rule. When the model contains errors, they are displayed in the Errors section at the bottom of the rule.

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