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3 Manage HCM Extract Definitions
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This topic describes the frequently used user entities and the type of data you can extract by using those user entities. You select user entities in the application when you define a data group. The following table lists the most frequently used user entities. Retrieves all persons across the enterprise and all person related attributes. Retrieves all workers and their payrolls across the enterprise, all person, worker, payroll related attributes, and element entry data. Retrieves assignment history as on the assignment effective start date.
Retrieves current and future person details. Specify advanced filter criteria to restrict person types. Reset the effective date contexts set dynamically by a parent data group using a runtime input parameter for the effective date.
For example, the Extract Assignment Basic History user entity sets the assignment effective start date as effective date first and then retrieves the data, unlike other user entities which use the effective date only.
If you want to use the Extract Assignment Basic History user entity to include the historical data but also want to change the effective date, then include the Reset Context user entity to reset this date using input parameters. Set up the Reset Context user entity as the root user entity to be a container or header.
For example, the following work structure elements: locations, positions, and legal employers are not related to each other. If you want to extract all of them in one single extract, then you can add them as child elements to the Reset Context user entity used as the root in the extract definition.
Adding this user entity as the root to these elements enables you to retrieve this data separately because the elements are not linked to a hierarchy.
You can view more details about the user entities using the View User Entity Details task.
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Retrieves assignment data as on the effective date. Retrieves assignment history as on the effective date. Retrieves current and future assignments. Use the Reset Context user entity in two ways: Reset the effective date contexts set dynamically by a parent data group using a runtime input parameter for the effective date.This example topic demonstrates how to create a HCM extract including creating data groups, records, and attributes using the Simplified interface.
FAST Bank is a global organization with subsidiaries all over the world. As part of an external reporting requirement, FAST Bank must obtain the department and employee details across the entire company. This information must be sent to a third party in an XML file and to the HR manager with employee details grouped by department as a Headcount Report.
The following table summarizes the key decisions in this scenario:. There are 2 functional groups of information, therefore you create two data groups, one for department and one for employees. You decide the number of records based on the subgroup of attributes within a data group. In this example, you create two records for the department data group:.
You decide the number of attributes based on the specific information required for that report. Create the following attributes for the Department Details record:.
Extract Record level to automatically generate formulas when you use the Generate Formula option. Use the Switch Layout button to open the extract in the Desktop interface. Use the Desktop interface to create and define HCM extracts without using a drag and drop system. You can perform most of the tasks for defining the extract in the Simplified interface. Yes By selecting this option you select this data group as the starting point for the extract execution.
An extract definition automatically creates an extract process payroll flow with the same name as the extract. The extract process enables you to define an execution sequence of multiple tasks, including before and after tasks. The following table summarizes the key decisions in this scenario: Decisions to Consider In This Example How many extracts do I create to produce this type of report?
You create one extract definition to define a headcount report. How many data groups do I create?
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How many records do I create? In this example, you create two records for the department data group: Department Details Department Summary You create one record for the employees data group: Employee Details.
How many attributes do I create? You can use fast formulas at the following levels: Extract Criteria level to determine certain conditions. Extract Rule level to derive attribute values. Extract Advanced Condition level to specify complex conditions. The application uses this name to generate the XML output file. Click Save. The application saves the extract definition and automatically generates the parameters based on the type of extract.
The parameters control the output of an extract. Using the drag and drop action, drag the Organizations object into the local area. This action automatically creates an associated record object. Creating Attributes Select the Departments Details record in the Department data group, and within the Configure icon select the Create Attribute option.
Defining the Delivery Options Select the Deliver icon and then the Add icon to define the delivery options. Submitting an Extract An extract definition automatically creates an extract process payroll flow with the same name as the extract.Payroll Interface Extract Definitions: Overview.Vtv v2 apk
Using the Simplified Interface: Worked Example. The HCM Extracts feature is a flexible tool for generating data files and reports.
This topic covers how you can use the extract components to define what information you want the application to extract and report on. It also explains how the application displays, formats, and delivers the information.
Fusion HCM Extracts
An extract definition refers to the complete setup of an extract, that consists of extract data groups, criteria, records, attributes, advanced conditions and output delivery options. An extract definition consists of:. One or more extract data groups, depending on how many logical entities you want to extract. One or more extract records depending on how many groups of information you want to collect.
One or more attributes depending on how many individual fields of data you want to collect. You can generate the output in the following formats:. You can distribute the extracted information by email, fax and other delivery modes.
Some common examples of extracts are: PDF payslips delivered to employees' mailboxes, payroll or benefits data transferred to third-party service providers, HR and talent data exchange between Oracle Fusion and legacy applications, for example in a coexistence scenario.
Extract data groups represent a business area or logical entity, for example person, assignment, or benefits. The application uses this information to retrieve the database item groups.
You define one data group as the primary or root data group and this data group is the starting point of the data extraction. Extract data group connections capture the association details between the current data group and the parent data group. The data group connections form the hierarchical relationship among the data groups. You can define a set of filtering conditions the application must perform on an extract data group using the extract data group criteria.
You specify the criteria conditions using an expression or fast formula. Extract records represent a grouping of related data or a physical collection of all fields required in the extract. An extract record is a collection of attributes which you can organize in a required sequence. For example, if a data group has 3 records, then you can specify the sequence in which the application processes the records.Guide for HCM Extracts.
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This document is not considered part of the applicable program documentation. Due to the nature of the product architecture, it may not be possible to safely include all features described in this document without risking significant destabilization of the code.Below is the agenda for this post. What is an HCM Extract? HCM Extracts is an outbound interfacing tool in Fusion. It is used to export large volumes of complex data into an output file XML. Features of HCM Extract. Types of HCM Extracts.
There are multiple types of HCM Extracts and depending upon our requirement we need to choose the right one. Navigation of HCM Extracts. On the right hand side tasks, we can see the tasks related to HCM Extracts.
Extract definition contains details of what data should be extracted and the structure in which data needs to be extracted, and how this data should be delivered. Refine HCM Extracts. When we create an extract, the application creates a flow pattern automatically, which includes a task for executing the extract. We can refine the flow by adding pre or post tasks that need to be executed along with data extraction.
Submit Extracts. Submit the extract for processing after entering the parameter values.
If the extract definition contains delivery options that specify an output format and delivery method email, ftp, etc. View Extract Results. We can see the results of Extract with success or error status.
We can also check the output files. View User Entity Details. We can see the user entity related Database items, contexts required, contexts set and the SQL query behind the user entity and finally the extracts using specific user entity. Architecture of HCM Extracts. A HCM Extract definition contains records grouping of attributes that contain multiple data elements attributes.
The extracted data is archived into result tables and stored as an XML output in the database. HCM Extracts Steps. Output Format and Delivery Options:. HCM Extract Modes. Security to use HCM Extract.
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