Published Release Notes

Configure the window size at run time in event strategies

You can now configure an Event Strategy rule to dynamically define the window size at run time by using a property value of the incoming record. To configure the window shape for dynamic size setting, you can use any property from the inheritance path that is available to the event strategy. This enhancement provides greater flexibility for strategy designers and broadens the scope of business scenarios in which event strategies can be applied.

For more information, see Event Strategy rule form - Completing the Event Strategy tab and Dynamic window size behavior.

Aggregate data in interaction history summaries

You can now group, aggregate, and filter interaction history data in a single strategy component. By using interaction history summaries, you can create refined data sets that simplify strategy frameworks and accelerate decision-making. Aggregated data sets are easier to process, manage, and troubleshoot.

For more information, see Data Sources landing page

New shape on the strategy canvas

The Strategy rule has been enhanced with the Embedded strategy shape, which simplifies the configuration of decisioning strategies that simultaneously apply to multiple types of audiences, for example, Devices, Households, and Subscribers. The Embedded strategy shape eliminates the need to switch between various classes to create a substrategy for each audience type that you want to target. Now, you can perform all configuration tasks on a single strategy canvas.

For more information, see Strategy components – Embedded strategy and Multilevel decisioning strategies.

New interaction history attribute

Pega^® Platform 7.4 introduces the pySubjectType attribute that is used in interaction history aggregations. This attribute is populated for interaction history records that were created in release 7.4. For records that originated in earlier releases, the attribute must be set in the following scenarios:

• Single-level decisioning frameworks that use interaction history.
• Multi-level decisioning frameworks where interaction history is used by two or more levels of strategies that are defined on different classes.

For the single-level scenario, configure the Dynamic System Setting that sets the pySubjectType attribute when your framework reads interaction history records. The value of this Dynamic System Setting becomes the name of the customer class.

For the multi-level scenario, update the database table for all strategy levels manually. For each level, make sure that the value in the Subject Type column is set to the name of the class for the corresponding strategy. For example, the value for the top level strategy should be set to the name of the class of that strategy.

For more information about interaction history aggregations, see Data Sources landing page

For more information about multi-line strategies and contexts, see Strategy components - Embedded strategy

HBase data set type becomes resumable

HBase data set has been enhanced to be resumable. As a result, data flow runs that reference the HBase data set as their primary data source are now resumable. You can pause and resume such data flow runs.

For more information, see the Resumability of data flow runs section in Data flow run updates.

Use repositories as sources for File data sets

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

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

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

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.

Upgrading Adaptive Decision Manager data mart tables might fail

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.