Extended proposition filter functionality
Valid from Pega Version 7.2.1
Multiple enhancements to the Proposition Filter rule type extend the functionality of proposition filters. When you configure the filter or the default behavior criteria in a proposition filter rule, you can select a strategy rule that contains an External Input shape. You can also apply the default behavior criteria to all incoming propositions that do not match the business issue or group defined in a proposition filter rule. Additionally, you can view the labels of when and strategy rules when you configure the filter or default behavior criteria.
For more information, see Proposition filter usability enhancements.
Import and export feature for generic decision data
Valid from Pega Version 7.2.1
New import and export functionality improves the management of generic decision data records (the records that do not belong to the Strategy Results class). You can now configure generic decision data records in a CSV file and later import that file to the Pega 7 Platform. You can also export the existing generic decision data record configuration from the Pega 7 Platform to a CSV file, and save that file in a directory that is external to the Pega 7 Platform.
For more information, see Decision data rule type enhancements.
Introduction of Customer Movie
Valid from Pega Version 7.2.1
Customer Movie provides the Event Catalog, where you can create multiple event types to collect customer data from specific input streams or batch uploads. This data is stored in a new type of data set called Event Store. Use the Customer Movie feature to make informed and personalized decisions for your customers, and to accelerate decisions.
For more information, see Creating an event in the Event Catalog.
Enhanced entity extraction with the CRF method
Valid from Pega Version 7.2.1
The Free Text Model rule now uses the Conditional Random Field (CRF) method for named entity extraction. The CRF method improves the accuracy of entity extraction by using sequence tagging and by reducing the number of false positives that were generated in the process of extracting named entities from the text. In addition, you can define your own custom entities and import them into the Pega 7 Platform as entity extraction rules that contain Rule-based Text Annotation (Ruta) scripts.
For more information, see Improved Free Text Model rule type.
Support for Twitter data recovery
Valid from Pega Version 7.2.1
You can configure a Twitter data set to use the new playback option to recover tweets that the system could not retrieve during a period of time in which tweets were unavailable, such as during a data flow failure. You can specify the time period for which you want to retrieve Twitter data and enter the maximum number of tweets that you want to retrieve.
For more information, see Improved Free Text Model rule type.
Time-based retrieval of Facebook posts
Valid from Pega Version 7.2.1
You can now control the amount of data that is retrieved from Facebook data sets by using the new search functionality for Facebook data set records. You can limit the retrieval of posts to any number of past weeks, days, hours, or minutes to get only the data that is relevant to your business objective or that you lost as a result of a system outage or failure.
For more information, see: Improved Free Text Model rule type.
Improved monitoring of data flow runs
Valid from Pega Version 7.2.1
To monitor the status, progress, and statistics of a data flow run, open it on the Data Flows landing page. Use the run and distribution details to report on data flow progress and possible service-level agreement (SLA) breaches. Run details are available at the node and partition level. Component-level statistics are available for the run, nodes, and partitions.
For more information, see the Data Flows landing page.
Adaptive learning without using an interaction ID
Valid from Pega Version 7.2.1
When you configure the Strategy shape in a data flow to capture the response to previous decisions, you do not have to provide an interaction ID. Instead, during the process of adaptive learning, adaptive models can query the Event Store data set over a specified period of time to retrieve decisions that were made for each response. This way, you eliminate the need to store the interaction ID on the client side.
For more information, see Delayed learning of adaptive models.
Single point of entry for decision management services configuration
Valid from Pega Version 7.2.1
Use the Services landing page to configure and monitor the Decision Data Store, Adaptive Decision Manager, Data Flow, and Visual Business Director services. This method simplifies decision management configuration because you can manage these services in one place.
For more information, see Services landing page.
Adaptive Decision Manager service in the Pega 7 Platform
Valid from Pega Version 7.2.1
The Adaptive Decision Management (ADM) service is now native to the Pega 7 Platform and is supported by the Decision data node infrastructure. Because of this enhancement, you no longer need to manage the ADM service as an external service. In addition, the ADM service does not require dedicated hardware or operating system environments.
For more information, see Services landing page.