Data Flow rule form
Completing Data Flows

Source is the standard entry point of a data flow. A source defines data you read from through the data flow.

• A data flow contains one primary source. This primary source can originate from:

  • Abstract: results in the data class.

  • Data flow: the entry point is based on another data flow. This data flow can be under the same data flow class or another class.

    Only a data flow that has an abstract destination can be used as the primary input in another data flow.

  • Data set: the entry point is based on the data defined in a data set in the data flow class.

  • Report definition: the entry point is based on a report definition. The scope of this report definition is the applies to class of the data flow. To distribute a data flow run across multiple nodes, select the Enable distributed run check box and specify the Partition Key.

    Note:  If you want to use a report definition that does aggregation (generates database group by statement), create a property in the class on which the report is defined. The property must have the same name as the aggregate in the report definition.

• Secondary sources are added as you start combining data. Secondary data sources can originate from a data set, data flow, or report definition.

The compose pattern allows you to combine data from two sources into a page or page list property. This pattern requires a property to match data between the two sources. The starting data point is the shape from which you start combining data. Once the compose path is available, you define the secondary source by providing an existing data set or another data flow.

The convert pattern allows you to take data in one class and put it in another, overwriting identical properties (by name), or explicitly mapping properties that do not have the same name between the source and target. This pattern requires a property to match data between the two sources. The data you pass is determined by the starting shape for the convert path. Once the convert path is available, you define its properties by selecting the target class and specifying how to handle property mapping between the source and target.

The mapping of properties between the source and target can be handled automatically, or you can explicitly define how to map source and target properties.

• Automatically means that properties in the source class override properties with the same name in the target class.
• Explicit mapping allows you to manage the mapping when you want to control which properties result in an overwrite, or you do not have properties with the same name, that represent the same data.

The event strategy pattern allows you to reference and run an event strategy in a data flow.

Configuring the event strategy pattern

1. In the Results in field, specify the name of the class containing your data flow.
2. In the Event strategy field, specify the name of the event strategy you want to use.
3. In the Properties output mapping section, map the properties from your event strategy to the properties that exist in the class containing your data flow.
1. Click Add Item.
2. In the Set field, specify a target property that exists in the class containing your data flow.
3. In the equal to field, specify a source property.

The filter pattern allows you to specify filter conditions and apply them to each element of the input flow. The output flow consists of those elements which satisfy the filter conditions.

Configuring the filter pattern

1. In the Name field, specify a name for your filter.
2. In the Filter conditions section, click Add Item.

3. In the left field, specify the name of a property to be used by the filter.

4. From the dropdown list, select a comparison operator.
5. In the right field, specify a value for your filter condition.

This pattern allows you to reference an instance of the Free Text Model rule to deliver text analytics capabilities to users via data flows.

The merge pattern allows you to combine data in the primary and secondary data paths into a single track. This pattern requires the source to be in the same class, matching conditions between the primary and secondary sources, and configuration to handle data mismatches. The starting data point is the shape from which you start merging data. Once the merge path is available, you define the secondary source by providing an existing data set or another data flow.

In cases of no data match, you can exclude the source component results that do not match the merge condition. If one of the specified properties does not exist, the value of the other property is not included in the class that stores the merge results.

In cases of data mismatch, you can select which source is leading:

• Primary path: if there are properties with the same name but different values, merge takes the value in the primary source.
• Secondary path: if there are properties with the same name but different values, merge takes the value in the secondary source.

The strategy pattern is designed to run a strategy based on combined or not combined data. The data that you pass to execute the strategy is determined by the starting shape for the strategy path. When the strategy path is available, you select the strategy to run and the mode in which to run it. In a data flow, each strategy can run in one mode only.

• Make decision - Use this mode when the strategy executed by the data flow is designed only to issue a decision.
• Make decision and store data for later response capture - Use this mode when the strategy executed by the data flow is designed to issue a decision and you want to store the decision results for a specified period of time. You can use this data for delayed adaptive model learning and issuing a response capture at a later time.
  • Store data for - Specify how long you want to store inputs passed to adaptive models and strategy results.
• Capture response for previous decision - Use this mode when the strategy executed by the data flow is designed to retrieve the adaptive inputs and strategy results. To retrieve decision results, you select one of the following options:
  • Identified by interaction ID - Enter the interaction ID for which you want to retrieve the adaptive inputs and strategy results.
  • In the past - Specify the time period from which you want to retrieve the adaptive inputs and strategy results.

Output strategy results

Unfold this section and select a class where you want to store strategy results.

• Individually in <class_name> - Use the strategy result class (default option).
• Updated in <class_name> - Use the input class of the strategy pattern as the output class.
• Embedded in - Enter any other class to store your strategy results.

When you decide to change the default output class, map the properties from the strategy result class to the properties of the class that you select.

The destination pattern defines the data point you write to and it is the standard output point of a data flow. Every data flow defines one or more destinations that output all results, or results based on a given condition.

The types of data representation you can use in a destination are: Abstract, Activity, Case, Data flow, and Data set.

The type of data set determines the write operation performed by the destination: Database tables, Decision Data Stores, Adaptive Decision Manager (ADM) by using the pxAdaptiveAnalytics data set, Interaction History (IH) by using the pxInteractionHistory data set, or a Visual Business Director (VBD) data source.

When your data set is a database table, you need to specify the save options:

• Only insert new records
• Insert new and overwrite existing records