Published Release Notes

Extension attributes are not supported in PMML models

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

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.

Decision Analytics portal renamed to Analytics Center

The Decision Analytics portal is renamed to the Analytics Center portal. In this work area for predictive analytics and text analytics, the business scientist can control the full model life cycle by building predictive models, importing PMML models, building sentiment analysis and text classification models, creating and monitoring adaptive models, and updating any existing models.

For more information, Analytics Center portal.

Ability to include all properties in search results

You can now include all properties in a class in search results so that they can be used in report filtering. When the Enable search results for all properties option is selected on the Custom Search Properties rule form, all top level and embedded page scalar properties for the class are indexed and returned in search results, and all embedded page list, page group, value list, and value group properties for the class are indexed but not returned in search results. Selecting this option might affect performance.

In addition, by default, properties defined in the Data-Tag-RelevantRecord instance for a class are indexed and returned in search results and do not need to be explicitly configured.

You must reindex search after selecting or clearing Enable search results for all properties and after changing the properties that are defined in the Data-Tag-RelevantRecord instance.

For more information, see Specifying custom search properties.

Support for controlling binary file upload in Pega Mobile Client

The Client Store API of Pega^® Mobile Client has been modified so that you can suspend and resume the process of uploading binary files to the server. You can also check the state of the file uploading process. As a result, custom mobile app users can process their work items without having to wait for the synchronization process to finish.

For more information, see Pega Mobile Client API methods for controlling binary data upload and Client Store API.

Support for large binary data item storage in Pega Mobile Client and offline case attachments in Pega Platform

Pega^® Mobile Client can now store and synchronize large binary data items and their corresponding actions from the action queue on Android and iOS devices. As a result, custom mobile app users can view, attach, and delete data files, whether the device is online or offline. For this function to work, you must enable offline case attachment support, which allows your custom mobile apps to synchronize case attachments between the Pega Platform and the mobile device.

For more information, see Enabling offline case attachments support and Client Store API.

Enhanced adaptive model reporting

The new Model report replaces the Behavior and the Performance overview reports to improve report usability and provide consistent information. You can export your Model reports into PDF or Excel files to view or share them outside the Pega® Platform. The Model report also includes information on the groups of correlated predictors where the best performing predictor from each group is active in the model and other remain inactive; this information helps you understand why predictors are active or inactive.

For more information, see Generating a model report.

Use Kinesis data sets in Pega Decision Management

You can create Kinesis data set instances to connect to Amazon Kinesis Data Streams and use this data set in decision management for processing real-time streaming data. Integrating Kinesis data streams into Pega® Platform in the cloud provides a fault-tolerant and scalable solution for processing IT infrastructure log data, application logs, social media, market data feeds, and web clickstream data.

For more information, see Creating a Kinesis data set.

Improvements in the process engine for offline-enabled applications

The offline process engine includes several improvements. To provide more options when you develop an offline-enabled application, a decision shape as the first shape in a flow and parameters for the CreateNewWork action are now supported. Offline-enabled applications now also display information about the last data synchronization.

For more information, see Flow processing in offline mode.

Store and scale the processing of Stream data records on multiple nodes

You can configure the Stream service on Pega^® Platform to ingest, route, and deliver high volumes of low-latency data such as web clicks, transactions, sensor data, and customer interaction history. You can store streams of records in a fault-tolerant way and process stream records as they occur. Add or remove Stream nodes to increase or decrease the use of the Stream service and optimize data processing.

For more information, see Stream service overview.