New aggregation functions in event strategies
Valid from Pega Version 7.3.1
You can use new functions in event strategies to build standard and complex aggregations. With new aggregation functions you can detect additional patterns in streams of data and deliver actionable insights.
For more information, see Adding aggregations in event strategies.
Continue batch data flow runs that failed and reprocess partitions with the failed records
Valid from Pega Version 7.3.1
You can now continue batch data flow runs that failed and complete them with failures. You can also identify all the records that failed during a batch data flow run that is completed with failures. After you fix all the issues that are related to the failed records, you can reprocess the failures by resubmitting the partitions that contain the failed records. This option saves time when your data flow run processes millions of records and you do not want to start the run from the beginning.
For more information, see Data flow run updates.
Data validation before importing
Valid from Pega Version 7.3.1
Data imported into a data type is now validated before it is imported. Validating data before importing it ensures that the data is valid and reduces the amount of time required to manually analyze and validate your data.
For more information about importing data into a data type, see Importing data for a data type.
Enable different REST service rules for distinct resource URIs
Valid from Pega Version 7.3.1
You can now specify different service REST rules for distinct resource URIs. This functionality provides different processing options, request handling, and response handling for each distinct resource URI. Additionally, it eliminates the need to develop and maintain complex logic to handle all possible resource URI paths.
For more information, see Distinct URI specification for service REST rules.
Decision Data Store and HDFS data set types become resumable
Valid from Pega Version 7.3.1
Decision Data Store (DDS) and HDFS data set have been enhanced to be resumable. As a result, data flow runs that reference Decision Data Store or HDFS data sets 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.
Integrate the intelligent interaction activity for text analytics into your application
Valid from Pega Version 7.3.1
Employ text analytics and machine-learning capabilities in multichannel applications by integrating the pyRunInteraction activity for content parsing and analysis. By calling this activity, you can automatically analyze any incoming text data, such as instant messages, posts, emails, and so on, to detect sentiments, categories, entities, or intents that can help you with automatic case creation and routing. For example, you can use this activity to populate case properties based on detected entities such as customer name, email address, and account number.
For more information, see Intelligent interaction in text analytics.
Update text analysis models during every interaction
Valid from Pega Version 7.3.1
While interacting with your customers through text-based communication channels (such as a Facebook chatbot or email), you can use an activity to provide feedback to a text analysis model by manually assessing whether the entities, categories, intents, and sentiments in the analyzed text were assigned to the expected class. By using this feedback input as training data, you can ensure that the accuracy of your text analytics models continuously improves.
For more information, see Feedback loop for text analysis.
Build predictive models with the genetic algorithm
Valid from Pega Version 7.3.1
A genetic algorithm solves optimization problems by creating a generation of possible solutions to the problem. In Pega® Platform you can utilize the functionality of genetic algorithms by using the genetic algorithm model in the Analytics Center portal. With this type of predictive model, you can create highly predictive, non-linear models by selecting the best performing model from the last generation.
For more information, see Creating models and Creating a genetic algorithm model.
The Run Data Flow shape replaces 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 to introduce a consistent way of making decisions and capturing responses. You can now run a single-case data flow by referencing the data flow in the Run Data Flow shape. The data flow must have an abstract input and abstract or dataset output.
For more information, see Running a decision strategy from a flow, About Data Flow rules and Interactions in flows are no longer supported by the Run Interaction shape.
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.