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Published Release Notes

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Browse resolved issues for Platform releases.

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

Control group configuration for predictions

Valid from Pega Version 8.5

You can now configure a control group for your predictions in Prediction Studio. Based on the control group, Prediction Studio calculates a lift score for each prediction that you can later use to monitor the success rate of your predictions.

For more information, see Customizing predictions.

Response timeout configuration for predictions

Valid from Pega Version 8.5

You can now set a response timeout for your predictions in Prediction Studio. By setting a response timeout, you control how Prediction Studio registers customer responses that later serve as feedback data for your predictions.

For more information, see Customizing predictions.

External data flow rules are deprecated

Valid from Pega Version 8.5

External data flows are now deprecated and no longer supported. To improve your user experience with Pega Platform™, the user interface elements associated with these rules are hidden from view by default. Identifying unused features allows Pega to focus on developing and supporting the features that you need.

For more information, see Deprecated: External data flows.

Visual Business Director data is automatically cleaned after a retention period expires

Valid from Pega Version 8.5

To avoid negative impact on system resources, such as memory and disk space, Pega Platform™ automatically cleans out collections data accumulated in Visual Business Director after the time period specified in the vbd/dataRetentionTimeout dynamic system setting.

Upgrade impact

In versions of Pega Platform earlier than 8.5, collections data was not automatically removed. From version 8.5, the data is removed after 465 days (15 months) by default.

What steps are required to update the application to be compatible with this change?

If the default data retention period does not meet your requirements, you can change it by editing the vbd/dataRetentionTimeout setting.

For more information, see "Configuring the data retention period for Visual Business Director" in the Pega Customer Decision Hub 8.5 Upgrade Guide on the Pega Customer Decision Hub product page.

Optimization check utility available for legacy strategies

Valid from Pega Version 8.5

Ensure that your strategies are compatible with the optimized strategy execution engine introduced in Pega Platform™ 8.1 by running a post-upgrade utility that checks strategies within your application for areas that you can optimize, for example, by reducing the number of page properties that are copied from one shape to another. Running the utility produces a report that you can use to plan the required updates to your strategies.

For more information, see Make your strategies compatible with the optimized strategy execution engine by using a check utility.

Uploading customer responses into adaptive models is no longer available

Valid from Pega Version 8.5

The option to train adaptive models by uploading a static list of historical interaction records has been deprecated in Pega Platform™ 8.5.

Upgrade impact

In versions of Pega Platform earlier than 8.5, it was possible to train an adaptive model by uploading historical data of customer interaction. After the upgrade to version 8.5, this option is no longer available.

What steps are required to update the application to be compatible with this change?

Use data from a report definition to train adaptive models. For more information, see Training adaptive models.

More flexibility for Date Time predictors in adaptive models

Valid from Pega Version 8.5

You can configure adaptive model predictors that indicate the amount of time that has elapsed since a particular event. In versions of Pega Platform™ earlier than 8.5, you could only specify the absolute date and time, for example, the date when a subscriber last visited one of your brick-and-mortar store locations. In Pega Platform 8.5, you can also indicate the amount of time that has passed, for example, the number of days since a subscriber purchased a new service plan.

For more information, see Adding a predictor to an adaptive model.

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