Published Release Notes

Language detection option in Text Analyzer

On the Text Analyzer form, you can identify the language of incoming records based on their language metadata tag by selecting the Language detected by publisher option. This option applies only to Text Analyzer rules that process Twitter records. By combining this option with the advanced language filtering criteria of Twitter data sets, you can filter out unnecessary data and analyze only the Twitter records that are relevant to your business objective.

For more information, see Configuring advanced filter conditions for Twitter data and Configuring language settings.

Facebook metadata types available for analysis

The number of Facebook metadata types available for analysis in your application through Facebook data sets has been extended. After you provide a valid page token that corresponds to your Facebook page, you can analyze the following metadata types that relate to that page: public posts, tagged posts, promoted posts, direct messages, and comments on posts. By analyzing these metadata types in your application, you can enhance your understanding of your customers' needs and respond to issues faster.

For more information, see Creating a Facebook data set record.

Options for filtering data in Twitter data sets

Twitter data sets have more options for filtering tweets. On the Advanced options tab of the Edit Data Set form, you can configure your Twitter data set to not analyze tweets if they contain specific keywords or if the tweets are made by specific authors. You can also select the languages to analyze based on the language metadata tag of the incoming tweets (tweets in other languages are ignored). By configuring the filtering criteria, you can ignore data that is not relevant to your text analysis and retrieve only the records that you need.

For more information, see Configuring advanced filter conditions for Twitter data.

Reconfiguration of the Adaptive Decision Manager service after upgrade to Pega 7.2.2

After you upgrade the Pega 7 Platform to version 7.2.2 from a version prior to 7.2,1, you need to configure the Adaptive Decision Manager service. Beginning with Pega 7.2.1, the Adaptive Decision Management (ADM) service is native to the Pega 7 Platform and is supported by the Decision data node infrastructure.

For more information, see Services landing page.

Predictive models can drive predictions

You can use predictive models as the basis of your predictions. As a data scientist, you can now use Machine Learning Operations (MLOps) to replace models in your system. You can 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 with MLOps.

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

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).

Improved processing of correspondence details

When you send correspondence, the system now does not update the pxSendDateTime property on the pxCorrSummary work page that belongs to pyWorkPage. In previous versions of Pega Platform™, after sending correspondence, the update of the pxSendDateTime property could cause errors when working with an application at run time. To prevent such issues, Pega Platform now includes a pyEnableCorrSummary when rule that, by default, is set to false. If your business scenario requires updating the pxCorrSummary work page, set the when rule value to true.

For more information, see:

• Notifying participants about events
• Approval by email
• Sending automatic emails from cases

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

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.

Questionnaires available in App Studio

App Studio now supports authoring questionnaires, which in previous releases of Pega Platform™ were known as surveys. You can create questionnaires, add question pages, and populate the pages with questions of different types so that you can collect the exact data that your business processes require. For more efficient data management and reuse, data objects from a data model now store answers to questions, instead of autogenerated properties. For example, when a customer provides a date of birth in a questionnaire, and your application stores the date as a data object, you can conveniently reuse that data object in related cases. For greater flexibility, both standard Pega Platform and Cosmos React applications support questionnaires, however, some question types are unavailable in Cosmos React.

For more information, see:

• Create questionnaires in a low-code way in App Studio (8.6)
• Creating a questionnaire

Remote case types in App Studio

App Studio now supports remote case types for applications that you build on Cosmos React. With remote case types, you can create a case type inside one application, and then work on cases based on this case type in another, remote application. As a result, users can perform work from multiple applications on one screen without the need to switch between applications, which results in increased efficiency and faster case resolution.

For more information, see:

• Increase efficiency by sharing remote case types between applications (8.6)
• Remote case types