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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.

Text predictions simplify the configuration of text analytics for conversational channels

Valid from Pega Version 8.6

Enable text analytics for your conversational channels, such as email and chatbot, by configuring text predictions that manage the text models for your channels. This new type of prediction in Prediction Studio consolidates the AI for analyzing the messages in your conversational channels in one place and replaces the text analyzer rule in Dev Studio.

Through text predictions, you can efficiently configure the outcomes that you want to predict by analyzing the text in your channels:

  • Topics (ticket booking, subscription cancellation, support request)
  • Sentiments (positive, neutral, negative)
  • Entities (people, organizations, airport codes)
  • Languages

You can train and build the models that predict these outcomes through an intuitive process, and then monitor the outcomes through user-friendly charts.

For more information, see Predict customer needs and behaviors by using text predictions in your conversational channels.

Upgrade impact

Channels that you configured with text analyzers in the previous version of your system continue to work in the same manner after the upgrade to the current version. When you edit and save the configuration of an existing channel, the text analyzer rule is automatically upgraded to a text prediction. The associated text prediction is now an object where you can manage and monitor the text analytics for your channel. When you create a new channel in the upgraded system, the system automatically creates a text prediction for that channel.

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

  1. Enable the asynchronous model building and reporting in text predictions through job schedulers that use the System Runtime Context (SRC) by adding your application to the SRC.
    For more information, see Automating the runtime context management of background processes.
  2. Enable model building in text predictions by configuring background processing nodes.
    For more information, see Assigning decision management node types to Pega Platform nodes.

External data flow rules are removed

Valid from Pega Version 8.6

In previous versions of Pega Platform™, you could configure data flows to run in an external Hadoop environment. The external data flows functionality was deprecated and hidden from view in Pega Platform 8.5. The functionality has been now removed and is no longer available in Pega Platform 8.6.

For more information, see External data flow rules are deprecated.

Insights from 8.5 require additional configuration after upgrade

Valid from Pega Version 8.6

Upgrade impact

After you upgrade Pega Platform™ version 8.5 to 8.6, the Explore Data landing page might not include insights that come from the earlier version of the product.

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

Run the pxUpgrade85Insights activity to make all insights from version 8.5 accessible for you in 8.6. By running this activity, you upgrade insights with new metadata that is required in version 8.6. For example, the pxUpgrade85Insights activity provides you with the option to set the visibility of insights to private, public or shared.

For more information about insights, see Visualizing data with insights.

Interactions in flows are no longer supported by the Run Interaction shape

Valid from Pega Version 7.3.1

The Run Interaction shape in flows has been replaced by the Run Data Flow shape, which supports running a single case data flow with a strategy. Flows that include the Run Interaction shape continue to work; however, you must now use the Utility shape to reference any new interactions that you create.

For more information, see Running a decision strategy from a flow and About Interaction rules.

Extension attributes are not supported in PMML models

Valid from Pega Version 7.3.1

Models in the Predictive Model Markup Language (PMML) format version 4.3 that contain extension attributes with the x- prefix are not valid. These extension attributes are deprecated; you must use extension elements instead. In addition, if the output type of any output field in the model is set to FLOAT, change it to DOUBLE.

For more information, see PMML 4.3 - General Structure in the Data Mining Group documentation.

The Upload responses action is not supported for adaptive models with customized context

Valid from Pega Version 7.3.1

A default instance of the Adaptive Model rule contains five model identifiers (.pyIssue, .pyGroup, .pyName, .pyDirection, .pyChannel) that are used to partition adaptive models. If you add other identifiers in your Adaptive Model rule instance, you cannot upload responses to this instance with the Upload Responses wizard and the following error is displayed: The Flow Action post-processing activity pzUploadCSVFile failed: Cannot parse csv file.You can still train such adaptive models with data flows.

For more information, see Training adaptive models in bulk with data flows, Model context, and Uploading customer responses.

Behavior changes when reporting on descendant classes

Valid from Pega Version 7.3.1

Report Definitions that use the Report on descendant class instances option with the Include all descendant classes option apply only to the Applies to Class. Join classes are not included as they were in previous Pega® Platform versions. The following example shows what happens for each possible scenario for Report on descendant class instances when the report is defined on ClassA with a class join with Work-.

  • If Report on descendant class instances is disabled, the report runs against ClassA and the join happens with Work-. The behavior is the same in Pega 7.3.1 as it is in previous Pega Platform versions.
  • If Report on descendant class instances is enabled, and Include single implementation class is selected, the report runs against ClassA and the join happens with the MySampleClass implementation class. The behavior is the same in Pega 7.3.1 as it is in previous Pega Platform versions.
  • If Report on descendant class instances is enabled, and Include all descendant classes is selected, the report runs against ClassA and its descendants and the join happens with Work-. In previous Pega Platform versions, the join happened with the MySampleClass implementation class.

Upgrading Adaptive Decision Manager data mart tables might fail

Valid from Pega Version 7.3.1

Issue: Upgrade from 7.3 to 7.3.1 fails if the data contained in the pxInsName column of the PR_DATA_DM_ADMMART_PRED_FACT table is longer than 128 characters.

Reason: During the Pega Platform™ upgrade from 7.3 to 7.3.1, data in the Adaptive Decision Manager (ADM) data mart tables is migrated from the PR_DATA_DM_ADMMART_PRED_FACT table to the PR_DATA_DM_ADMMART_MDL_FACT table. In Pega 7.3.1, ADM uses only the PR_DATA_DM_ADMMART_MDL_FACT table where the pxInsName property can store values that are 128 characters long. In Pega Platform 7.3, the pxInsName property in the PR_DATA_DM_ADMMART_PRED_FACT table can store values that are 255 characters long. If the pxInsName property contains values that are longer that 128 characters, the upgrade fails.

Resolution: Issue an ALTER TABLE statement to change the pxInsName column size to 255 characters and resume the upgrade. For example:

ALTER TABLE rules.pr_data_dm_admmart_pred ALTER COLUMN pxInsName TYPE varchar(255);

For more information, see Adaptive Decision Manager data model.

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