36Managing HCM Extracts

This chapter contains the following:

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.

Extract Definitions

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 use HCM extracts to extract, archive, transform, report, and deliver high volumes of HCM data from the Oracle Fusion HCM database. You can generate the output in the following formats:

  • CSV

  • XML

  • Excel

  • HTML

  • RTF

  • PDF

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.

Data Groups

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

Extract records represent a grouping of related data or a physical collection of all fields required in the extract. For example, the Employee data group can have records such as Basic Details, Pay Details, Location Details, and Primary Contact. 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. You can also select the next data group to identify which data group the application processes next.

Attributes

Attributes are the individual fields inside the extract record. An attribute is the lowest attribute level of a HCM extract and represents a piece of information, for example, person first name, person last name or person date of birth.

This figure demonstrates the hierarchy of information within a data group definition.

Hierarchy of data objects within an extract definition.

The type of extract you select determines the purpose of the extract. It also determines the parameters that are automatically generated. For example, if you select the Payroll Interface extract type, then the application creates a changes only parameter, as well as the other parameters. You can select the extract type on the Extract Definitions page.

This table lists the different extract types and why you select them.

Extract Type Purpose

Full Profile

Use for complete employee and payroll data archives.

Payroll Interface

Use for providing data to third party payroll service providers.

Payments

Use for salary payment method archives. For example, Paid through cheque or bank transfer.

Benefit Carrier

Use for providing data to third party benefits service providers.

Archive Retrieval

Use for reports based on permanently archived data, for example, payslip.

EOY Archive

Use for end of year archives (HR, Benefits).

HR Archive

Use for all HR archives.

Payroll Archive

Use for all payroll or payslip archives.

Other Payroll Archive

Use for all payroll archives.

Overview of Payroll Interface Extract Definitions

The extract definitions of the Payroll Interface extract type determine the data you send your third-party payroll provider. This table lists the predefined Payroll Interface extract definitions that you can use or define to meet your business-specific extract requirements.

Extract Definition Purpose Output

Global Payroll Interface

Derives payroll data either from element entry values or from balance results that the Calculate Gross Earnings process creates.

eText and XML

Payroll Interface for NGA

Extracts general-purpose HR and payroll-related data to integrate with Payroll Exchange for third-party payroll processing by NGA Human Resources. This extract transforms the data into an HR-XML format compliant with NGA Human Resources standards.

Use the predefined Run Payroll Interface Report for NGA process if you don't require special modifications.

XML

US ADP PayForce Third-Party Ad-Hoc Extract

Derives payroll data from element entries, including common HR and payroll data for a date range or a payroll period. Output format is compliant with Automatic Data Processing (ADP) PayForce standards.

eText and XML

US ADP PayForce Third-Party Periodic Extract

Derives payroll data from balance results that the Calculate Gross Earnings process creates for a payroll period. Output format is compliant with ADP PayForce standards.

eText and XML

When creating an extract definition, you need user entity details to create data groups. You can access the User Entity Details UI using the Data Exchange tasks pane or when you create a data group in the Design tab of the Extract Definitions task.

Using the User Entity Details page, you can:

  • View the database items available in a user entity.

  • Validate user entities for use with root data groups.

  • Review the type of user entity, for example, single row, multiple rows, historic, or effective dated.

  • Review the SQL query the user entity uses.

  • Calculate the number of rows in a data set.

  • Review the contexts used and set by the user entity.

  • Verify the extracts that are using the user entity.

The following sections detail the information that you can derive from the User Entity Details UI.

Review the User Entity Details

Search for a user entity in the User Entity Details UI and click the User Entity Details tab.

If the value of Valid for Root Data Group is Yes, the user entity can be used as a root data group. You can also determine if a user entity is valid for use as a root data group, if the value of Multiple Rows is Yes and Context Required is No. For example, the PER_EXT_SEC_PERSON_UE user entity can be used as a root data group, as the value of Multiple Rows is Yes and Context Required is No.

If a user entity is not a multiple row user entity, you must not use it as the root data group. If a multiple row user entity sets the contexts required for a single row user entity, the database item groups from the single row user entity are generally included as derived database item groups to the multiple row user entity. For example, the PER_PER_PERSON_DETAILS_UE user entity is not a multiple row user entity.

If a user entity is historic, it retrieves data irrespective of the effective date. For example, the PER_EXT_ASSIGNMENT_BASIC_HISTORY_UE user entity retrieves the entire historic details of an assignment.

If a user entity is not historic, it retrieves data as of the effective date. For example, the PER_EXT_PAY_EMPLOYEES_UE user entity retrieves Person, Assignment, and Payroll details as of the effective date.

Review the SQL query

In the User Entity Details UI, search for a user entity and click the Query tab. This tab lists the SQL query that the user entity uses to extract data. You can review the table structure and aliases which is useful for creating advanced filter criteria. If the user entity is valid as a root data group, you can calculate the rows that the SQL query will return. However, the number of rows returned is an estimate and may not match the exact number of rows the extract will return. The actual extract output depends on the filter criteria, expressions, and fast formulas used in the extract.

Review the User Entity Contexts

In the User Entity Details UI, search for a user entity and click the Context tab. The Contexts Required section lists the contexts that you have to set to use the user entity in the extract. For example, the PER_PER_PHONES_UE user entity requires the PERSON_ID context; therefore, you must set the PERSON_ID context to use this user entity. Generally, the user entities that are not historic require the EFFECTIVE_DATE context. However, the EFFECTIVE_DATE context is set by default, so you do not have to set this context explicitly. The Contexts Set section lists the contexts that are set by the user entity. For example, the PER_EXT_SEC_PERSON_UE user entity sets the PERSON_ID, ORGANIZATION_ID, and ENTERPRISE_ID contexts that can be used by other user entities.

Verify Extracts Using the User Entity

In the User Entity Details UI, search for a user entity and click the Extracts Using User Entity tab. If another extract is using the user entity, you can review the extract design to understand how the user entity is being used. You can also copy the extract design and then modify it to suit your needs.

A user entity is a logical entity associated with a data group defined using HCM extracts. 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.

User Entity Name and Code Description

Person (PER_EXT_SEC_PERSON_UE)

Retrieves all persons across the enterprise and all person related attributes.

Worker Payroll (PER_EXT_PAY_EMPLOYEES_UE)

Retrieves all workers and their payrolls across the enterprise, all person, worker, payroll related attributes, and element entry data.

Extract Assignment Basic History (PER_EXT_ASSIGNMENT_BASIC_HISTORY_UE)

Retrieves assignment history as on the assignment effective start date.

Extract Assignment Basic Information (PER_EXT_SEC_ASSIGNMENT_BASIC_UE)

Retrieves assignment data as on the effective date.

Assignments Range (PER_EXT_SEC_ASSIGNMENT_RANGE_UE)

Retrieves assignment history as on the effective date.

Extract Current and Future Persons (PER_EXT_SEC_PERSON_NOW_FUTURE_UE)

Retrieves current and future person details. Specify advanced filter criteria to restrict person types.

Extract Current and Future Assignments (PER_EXT_SEC_ASSIGNMENT_NOW_FUTURE_UE)

Retrieves current and future assignments.

Reset Context (PER_EXT_RESET_UE)

Use the Reset Context user entity in two ways:

  1. 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.

  2. 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.

Use the predefined Work Structure and Worker extract templates to quickly set up extracts that generate work structure and worker details. The Work Structure extract generates details of business units, legal entities, departments, grades, jobs, locations, and positions. The Worker extract generates details of person names, phones, emails, national identifiers, address, legislative data, accruals, absences, work relation, work term, assignment, work measure, supervisor, and salary.

To use these extracts, copy and configure them to suit your needs. You must not run the extract template directly. These extracts are complex and detailed. They can extract a huge volume of data and can be time consuming as they are designed on historic user entities to return all the details irrespective of the effective date.

When using these extract templates, ensure the following to avoid unneeded and time consuming data retrieval:

  • Define filter criteria. For example, if you want to extract data related to specific locations, include an expression or fast formula in the data group filter conditions.

  • Remove unwanted data groups. For example, if you are not interested in positions, then you can remove the positions data group.

  • Review all the details to ensure all the information is relevant to your needs.

Using Work Structure and Worker Extract Templates

To use the Worker or Work Structure extract templates:

  1. Copy the Worker or Work Structure extract definition to create a new extract.

  2. Update the copied extract.

  3. Generate and compile fast formulas.

  4. Validate the extract design.

  5. Refine the parameters.

This example demonstrates the steps required to create an extract definition using the Desktop interface. You can access the Desktop interface by clicking the Switch Layout button on the Manage HCM Extract Definitions page. Before you create an extract definition, you should understand the following details:

  • Information that you want to extract

  • Structure in which the data must be extracted

  • How you want to deliver this data (including file format, delivery mechanism, and frequency information)

FAST bank is a global organization with subsidiaries all over the world. As part of an external business reporting requirement, FAST bank is required to extract the department and employee details (grouped by department) across the entire company. This information must be sent to a third party in an XML file and to HR Managers in a PDF file using email. 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?

There are 2 functional groups of information, therefore you create two data groups, one for department and one for employees.

How many records do I create?

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:

  • Department Details

  • Department Summary

You create one record for the employees data group: Employee Details.

How many attributes do I create?

You decide the number of attributes based on the specific information required for that report. Create the following attributes for the Department Details record:

  • Department Name

  • Department Location

For the Department Summary record, create the following attributes:

  • Record Code

  • Report Date

  • Employee Count

For the Employees Details record, create the following attributes:

  • Full Name

  • Gender

  • Date of Birth

  • Salary

  • Bonus

  • Tax Rate

Do I create any fast formulas?

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.

  • Extract Record level to automatically generate formulas when you use the Generate Formula option.

Creating an Extract Definition

  1. On the Extract Definitions page, click the Add icon.

  2. Enter 01-Jan-2000 as the Session Effective Date.

    The session effective date is an effective start date that applies to all date-effective interactions in the current session.

  3. Enter FAST Bank Extract as the name and select HR Archive as the type. The application automatically creates the tag name based on the extract name and uses this name to generate the XML output file.

  4. Click OK. 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. In this example, the application creates the following parameters:

    • Effective Date

    • Legislative Data Group

    • Parameter Group

    • Report Category

    • Request ID

    • Start Date

Create Data Groups

  1. Select the Data Group link from the Hierarchy to open the Data Groups region.

  2. Click the Add icon to define a new data group.

  3. Complete the fields to create a data group, as shown in this table:

    Field Name Entry

    Name

    Departments

    User Entity

    PER_EXT_SEC_ORGANIZATION_UE

    Root Data Group

    Yes (By selecting this option you select this data group as the starting point for the extract execution.)

  4. Select Save and Create Another to create a data group for Employees.

  5. Complete the fields to create a data group, as shown in this table:

    Field Name Entry

    Name

    Employees

    User Entity

    PER_EXT_SEC_ASSIGNMENT_UE

    Root Data Group

    No

Create Extract Data Group Connections

  1. Select Data Group in the Hierarchy to display the data groups in a table.

  2. Select the Employees Data Group and define the data group connection details.

  3. Complete the fields to create a data group connection, as shown in this table:

    Field Name Entry

    Parent Data Group

    Departments

    Parent Data Group Database Item

    PER_EXT_ORG_ORGANIZATION_ID

    Data Group Database Item

    PER_EXT_ASG_ORG_ID

  4. Define the data group criteria for each data group.

Create Extract Records

  1. Select the Departments Data Group from the Hierarchy and select the Add icon in the Records region. Extract records represent a physical collection of all required fields. If a data group has 3 records, then you can specify the sequence in which the application processes the records using the sequence field. You can also select the Next Data Group to identify which data group the application processes next.

  2. Create two records for the Departments data group.

  3. Complete the fields to create two records for the Departments data group, as shown in this table:

    Field Department Summary Department Details

    Name

    Department Summary

    Department Details

    Effective Start Date

    1/1/00

    1/1/00

    Sequence

    20

    10

    Type

    Trailer Record

    Header Record

    Process Type

    Fast Formula

    Fast Formula

    Next Data Group

    NA

    Employees

  4. Save the records, then select the Employees data group and select the Add icon in the Records region.

  5. Create one record for the Employees Data Group.

  6. Complete the fields to create a record for the Employees data group, as shown in this table:

    Field Name Entry

    Name

    Employee Details

    Effective Start Date

    1/1/00

    Sequence

    10

    Type

    Detail Record

    Process Type

    Fast Formula

Create Attributes

  1. Select the Departments data group from the Hierarchy and select the Department Details record.

    An extract attribute is an individual field of a record.

  2. Create the following extract attributes for the Department Details record and select Save.

  3. Complete the fields to create extract attributes for the Department Details record, as shown in this table:

    Field Name Attribute Entry Attribute Entry

    Name

    Department Name

    Department Location

    Type

    Database item group

    Database item group

    Database Item Group

    Organization Name

    Organization Location Country

  4. Save the record, then select the Department Summary record.

  5. Select the Add icon in the Extract Attributes region.

  6. Create the following extract attributes for the Department Summary record and select Save.

  7. Complete the fields to create extract attributes for the Department Summary record, as shown in this table:

    Field Name Attribute Entry Attribute Entry Attribute Entry

    Name

    Record Code

    Report Date

    Employee Count

    Data Type

    Text

    Date

    Number

    Type

    String

    Parameter Element

    Summary Element

    String Value

    999

    NA

    NA

    Parameter

    Effective Date

    NA

    NA

    Aggregate Function

    NA

    NA

    Count

    Aggregate Record Name

    NA

    NA

    Employees Employee Details

  8. Select the Employees data group from the Hierarchy and select the Employee Details record.

  9. Create the following extract attributes for the Employee Details record and select Save.

  10. Complete the fields to create extract attributes for the Employee Details record, as shown in this table:

    Field Name Attribute Entry Attribute Entry Attribute Entry

    Name

    Full Name

    Gender

    Date of Birth

    Start Date

    1/1/00

    1/1/00

    1/1/00

    Data Type

    Text

    Text

    Date

    Type

    Database Item Group

    Decoded database item group

    Database item group

    Database Item Group

    Person Full Name

    Person Gender

    Person Date of Birth

  11. Complete the fields to create more extract attributes for the Employee Details record, as shown in this table:

    Field Name Attribute Entry Attribute Entry Attribute Entry

    Name

    Salary

    Bonus

    Tax rate

    Start Date

    1/1/00

    1/1/00

    1/1/00

    Data Type

    Number

    Number

    Text

    Type

    Database item group

    Record Calculation

    Rule

    Database Item Group

    Assignment Salary Amount

    NA

    NA

    Calculation Expression

    NA

    Salary * 0.5

    NA

    Rule

    NA

    NA

    FAST Bank Tax Rule

Define the Delivery Options

  1. Navigate to the Extract Execution Tree to validate the extract definition setup.

  2. Select Export XML Schema to download the XML Schema Definition (.XSD) file for this extract setup. This exported file contains the structure of the extract definition: the data groups, records, and attributes.

  3. Select Extract Delivery Options in the Hierarchy to define the formatting and layout options for the extract definition.

  4. Complete the fields for the delivery options, as shown in this table:

    Field Value Value

    Start Date

    1/1/00

    1/1/00

    End Date

    12/31/12

    12/31/12

    BI Publisher Template

    ReportLayout

    EFTLayout

    Output Type

    PDF

    EFT

    Delivery Type

    Email

    FTP

    Delivery Option Name

    Email to HR

    FTP to 3rd Party

    Output Name

    HeadcountReport

    EFTReport

  5. Define further information for each delivery option in the Additional Details region. For example, add the server, username and password for the FTP delivery type.

  6. Enter FAST Bank Extract as the reporting category and click Submit.

Submit an Extract

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.

  1. Select the Submit Extracts task and select the FAST Bank Extract process.

  2. Select Next.

  3. Enter FAST Bank Extract - Jan 2012 as the Payroll Flow (extract process).

  4. Enter 1/1/15 as the End Date.

  5. Select Next. You can specify interaction details if the task is dependent on other tasks with different extract processes. For example, this task must wait because another task is running.

  6. Select Next and review the extract. You can schedule the extract, or run it immediately.

  7. Select Submit.

  8. Select OK and View Checklist to view the status of the process.

  9. Select the View Extract Results task to review the results of the extract run. Search for the FAST Bank Extract process.

  10. Select Go to Task for FAST Bank Extract - Jan 2012, click the eyeglasses, and view the report output by selecting the report name.

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:

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?

There are 2 functional groups of information, therefore you create two data groups, one for department and one for employees.

How many records do I create?

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:

  • Department Details

  • Department Summary

You create one record for the employees data group: Employee Details.

How many attributes do I create?

You decide the number of attributes based on the specific information required for that report. Create the following attributes for the Department Details record:

  • Department Name

  • Department Location

For the Department Summary record, create the following attributes:

  • Record Code

  • Report Date

  • Employee Count

For the Employees Details record, create the following attributes:

  • Full Name

  • Gender

  • Date of Birth

  • Salary

  • Bonus

  • Tax Rate

Do I create any fast formulas?

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.

  • Extract Record level to automatically generate formulas when you use the Generate Formula option.

Create an Extract Definition

  1. On the Extract Definitions page, click the Add icon.

  2. Enter FAST Bank Extract as the name, 01-JAN-2010 as the Start Date, and select HR Archive as the type. The application uses this name to generate the XML output file.

  3. Click OK. 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.

    Use the Edit icon 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.

Create Extract Data Groups and Records

  1. Select the Design icon to create the data groups and records.

  2. Create the data group with the following information:

    Field Name Entry

    Name

    Departments

    User Entity

    PER_EXT_SEC_ORGANIZATION_UE

    Root Data Group

    Yes (By selecting this option you select this data group as the starting point for the extract execution.)

  3. Right-click the Departments data group in the Object Name table and select Add Record.

  4. Complete the fields to create two records for the Departments data group, as shown in this table:

    Field Department Summary Department Details

    Name

    Department Summary

    Department Details

    Effective Start Date

    1/1/00

    1/1/00

    Sequence

    20

    10

    Type

    Trailer Record

    Header Record

    Process Type

    Fast Formula

    Fast Formula

    Next Data Group

    NA

    Employees

  5. Select Save and Close. Create another data group by right-clicking the Departments data group and select Add Child Data Group.

  6. Update the data group with the following information:

    Field Name Entry

    Name

    Employees

    User Entity

    PER_EXT_SEC_ASSIGNMENT_UE

    Root Data Group

    No

  7. Right-click the Employees data group in the Object Name table and select Add Record.

  8. Complete the fields to create a record for the Employees data group, as shown in this table:

    Field Name Entry

    Name

    Employee Details

    Effective Start Date

    1/1/00

    Sequence

    10

    Type

    Detail Record

    Process Type

    Fast Formula

Create Extract Data Group Connections

  1. Select the Connect Data Groups tab on the Employees data group, and select the Add icon to add a connection.

  2. Complete the fields to create a data group connection, as shown in this table:

    Field Name Entry

    Parent Data Group

    Departments

    Parent Data Group Database Item

    PER_EXT_ORG_ORGANIZATION_ID

    Data Group Database Item

    PER_EXT_ASG_ORG_ID

  3. Define the data group filter criteria for each data group by selecting the Filters tab.

Create Attributes

  1. Select the Departments Details record in the Departments data group, select the Attributes tab, and then the Add icon.

  2. Complete the fields to create extract attributes for the Department Details record, as shown in this table:

    Field Name Attribute Entry Attribute Entry

    Name

    Department Name

    Department Location

    Type

    Database item group

    Database item group

    Database Item Group

    Organization Name

    Organization Location Country

  3. Select the Department Summary record, and using the above method enter the following extract attribute details.

  4. Complete the fields to create extract attributes for the Department Summary record, as shown in this table:

    Field Name Attribute Entry Attribute Entry Attribute Entry

    Name

    Record Code

    Report Date

    Employee Count

    Data Type

    Text

    Date

    Number

    Type

    String

    Parameter Element

    Summary Element

    String Value

    999

    NA

    NA

    Parameter

    Effective Date

    NA

    NA

    Aggregate Function

    NA

    NA

    Count

    Aggregate Record Name

    NA

    NA

    Employees Employee Details

  5. Select the Employee Details record within the Employees data group and using the same method enter the following extract attribute details.

  6. Complete the fields to create extract attributes for the Employee Details record, as shown in this table:

    Field Name Attribute Entry Attribute Entry Attribute Entry

    Name

    Full Name

    Gender

    Date of Birth

    Start Date

    1/1/00

    1/1/00

    1/1/00

    Data Type

    Text

    Text

    Date

    Type

    Database Item Group

    Decoded database item group

    Database item group

    Database Item Group

    Person Full Name

    Person Gender

    Person Date of Birth

Define the Delivery Options

  1. Select the Deliver icon and then the Add icon to define the delivery options.

  2. Complete the fields for the delivery options, as shown in this table:

    Field Value Value

    Start Date

    1/1/00

    1/1/00

    End Date

    12/31/12

    12/31/12

    BI Publisher Template

    ReportLayout

    EFTLayout

    Output Type

    PDF

    EFT

    Delivery Type

    Email

    FTP

    Delivery Option Name

    Email to HR

    FTP to 3rd Party

    Output Name

    HeadcountReport

    EFTReport

  3. Ensure you enter the additional information such as, the server, username, and password for the FTP delivery type.

  4. Enter FAST Bank Extract as the reporting category and click Submit.

  5. View the extract definition details and ensure the structure is valid in the Validate page by selecting the Validate button.

  6. Select Export XML Schema to download the XML Schema Definition (.XSD) file for this extract setup. This exported file contains the structure of the extract definition: the data groups, records, and attributes.

Submit an Extract

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.

  1. Select the Submit Extracts task and select the FAST Bank Extract process.

  2. Select Next.

  3. Enter FAST Bank Extract - Jan 2012 as the Payroll Flow (extract process).

  4. Enter 1/1/15 as the End Date.

  5. Select Next. You can specify interaction details if the task is dependent on other tasks with different extract processes. For example, this task must wait because another task is running.

  6. Select Next and review the extract. You can schedule the extract, or run it immediately.

  7. Select Submit.

  8. Select OK and View Checklist to view the status of the process.

  9. Select the View Extract Results task to review the results of the extract run. Search for the FAST Bank Extract process.

  10. Select Go to Task for FAST Bank Extract - Jan 2012, click the eyeglasses, and view the report output by selecting the report name.

Use the Validate feature in the Extract Definitions task to ensure the data you enter in the Design tab is valid and there are no issues when you submit. After creating an extract, go to the Validate tab and click Validate. If there are any issues in the extract design, validation messages are displayed.

Validate Extracts

When you validate an extract, the application performs validations on the extract design to ensure that:

  • The root data group is defined.

  • All non-root data groups are linked to the root data group directly or indirectly (for example, through another non-root data group that is linked to the root data group).

  • If a sequence of data groups is defined, then the next data group is also defined for processing.

  • All Fast Formulas used in the extract exist and are compiled or valid.

  • There are no issues detected during BI Publisher validations.

If the validation is successful, the application marks the extract as valid. However, if the validation fails, the application marks the extract as invalid and submitting the extract results in errors.

Using the View Extract Results task, you can review extract run information and troubleshoot extract runs that are unsuccessful or have not produced the expected results. In the Search area, use the various filters available to search the extract or extract run. In the Search Results area, click the extract run that you want to analyze.

In the View Extract Run Details page, you can review the following information:

  • Parameters

  • Archive details

  • Process details

  • Changes Only Details

  • Delivery options

Parameters

The Parameters tab displays the parameters set for the extract run. For example, Baseline Only, Changes Only, Process Start Date, Process End Date, Process Configuration Group, and so on. You can also export these parameters to an Excel Spreadsheet.

Archive Details

The Archive Details tab displays the number of records that were extracted by the extract run.

Process details

The Process Details tab lists the processes and their hierarchy. You can view the process status, start and finish time, and the elapsed time. You can also download the process log files, which can help you troubleshoot failed or time consuming extract runs.

Extract Delivery Options

The Delivery Options tab is visible only if you have set the delivery option in the Extract Definitions task as WebCenter Content or Inbound Interface. If the extract run is submitted and completed successfully, you can also download the output file.

Changes Only Details

Use the Changes Only Details tab to review the change in an attribute from the last successful run. This tab is visible only when the extract is run in the Changes Only mode. You can verify if the Changes Only parameter was set in the Parameters tab. Select the attribute and enter the attribute value to check the change in the attribute from the last successful run.

Purge Extracts Archive Information

You can remove redundant archive data to free up space and improve overall performance in your database. Use the Purge Extracts Archive Data process to remove the unnecessary information.

Here's how you can purge the redundant extracts archive information:

  1. Select and search Purge Extracts Archive Data job under Scheduled Processes. The archive data includes the associated payroll actions, object actions, and action information rows generated by extracts.

  2. In the Process Details page, define the criteria for the purge process by selecting the appropriate values for the process parameters.

    Parameter Name Values Default Value

    Report Mode

    Yes/No

    • Yes: Provides details of the archive data you want to purge

    • No: Purges the archive data generated by the selected Extract List

    Yes

    Extract List

    Lists the extracts to purge or generate a report

    N/A

  3. Click Submit.

  4. You can search for the job and check the completion status with any scheduled processes.

  5. If you execute the process in Report Mode, the output file provides a report including these details:

    • Extract definition Name

    • Extract Type

    • Archive data count

    • Storage recovered by the purge process

  6. Use the details in the report to identify data that you want to clean up from the application.

    Note: You can run only one instance of this ESS job at any time.

FAQs for Managing Extracts

When you create or import an extract, make sure you keep the Changes Only check box selected. This option creates an extract that captures the incremental changes only and not a full extract. The Changes Only option automatically adds the Changes Only parameter to the extract. When you run the extract, you can set the value of the parameter to capture changes. The extract generates the current status of the data, compares it with the baseline data from previous runs and identifies anything new and any modifications.

Remember that you also need to set up threading database details to fully implement the changes only behavior.

What's the Simplified interface in HCM Extracts?

The Simplified interface is an easy-to-use graphical interface for defining and designing HCM extracts. You can perform most of the tasks for defining the extract in the Simplified interface, however to enter an effective date, you must use the Desktop interface.

Data group connections enable you to define the master-detail of parent-child relationship between the entities. For example, the Employees and Departments data groups are linked with Department ID.

You can see the difference between the Always Display and the Mark as Changed attributes when you have a parent child relationship in the extract. If an attribute is set as Mark as Changed, and a change occurs on the same record, then the application includes this attribute in the output. If no attributes change on the record, but an attribute changes in another record, for example a parent or sibling record, then the application does not include the attribute in the output.

If an attribute is set as Always Display and a change occurs on the record or in the hierarchy below the record, then the application includes this attribute in the output. The application includes the attribute even if there are no changes in the attribute's record. If there is a change beneath the record, then it's included.

You can disable an extract by using the Extract Definitions task in the Data Exchange area. Search for and open the extract that you want to disable. Change the status of the extract to Inactive. After disabling an extract, you cannot submit the extract run again. The previous submitted runs of a disabled extract are stored and are available for review.

Probably because it's a payroll or seeded localization extract which is Legislative Data Group (LDG) enabled and you're looking in the Data Exchange work area. Search for your extract by LDG using the Show Filters option in the Extracts Definitions UI. You need to use the Payroll>Checklist work area to submit these types of extracts.

How can I keep an extract safe from unwanted edits?

Keep an extract locked to ensure no edits are made while the extract is in use. The lock feature can help you avoid situations such as a Changes Only extract being edited while in use and resulting in a full run extract.

Find the Lock Definition option and the Unlock Comments field on the Define page. The extract definition must be valid before you lock it and you must provide a reason before you can unlock it. Unlock the extract definition if it does require a change by providing a justification.

Why can't I submit an extract run?

You can't submit an extract run when:

  • The status of the extract is inactive. An inactive extract indicates that it's disabled. To submit an extract run, the status must be Active. Inactive extracts are not available for submission in the Submit Extracts task.

  • The extract is invalid. After creating an extract, if you validate it and there are some validation errors, the extract is marked as invalid. If you try to submit an invalid extract, the process fails and errors are displayed. Resolve the validation errors and validate the extract. Then submit the extract run again.

You can't find the inactive extracts because by default, the search results display active extracts only. To view inactive extracts, use the Extract Definitions task in the Data Exchange work area. In the Extract Definitions page, select Show Filters, Inactive in the Status drop-down list and click Search.

If you want the search results to display both active and inactive extracts, select the blank option in the Status drop-down list.

No. It's not required to validate existing extracts. Extracts that are not validated are marked as Not Yet Validated. You can submit extracts that are not validated. However, if there are issues with the extract design, then errors may occur or the result data may be incorrect. To avoid any errors, ensure that you validate the extract before submitting.

Use the View Extract Results task. Search for the extract and select an extract run. In the Details area, the Process Details tab lists the extract run processes. You can download the log file for any process using the Log column. You can review the log files to identify the records that did not retrieve the expected data and to identify time consuming processes.

Search for the user entity in the User Entity Details UI. If it is a multiple row user entity and does not require any context, you can use this user entity as the root data group.

You can access the User Entity Details UI:

  • From the Data Exchange tasks pane.

  • When creating a data group in the Design tab of the Extracts Definitions task.

Yes. Use the Include changes from last successful run option to exclude the extract runs that did not complete successfully when you run a changes only extract. Leave the option unchecked if you want the application to include both the archives from extract runs that completed successfully and those that completed unsuccessfully when you run a changes only extract.

Use the Baseline Only parameter in your extract to create a baseline for which you can run all subsequent changes only extracts against. This parameter can save time when running the extract because it doesn't generate an XML file and it doesn't deliver any output. You set the Display option to Yes or Mandatory for the Baseline Only parameter. It creates a full extract in less time and uses less storage in your application.

Yes. When you create a full extract of data, use the Delete Archive parameter to give you the flexibility of deleting archive and XML files at a later date. Set the Display option to Yes or Mandatory for the Delete Archive parameter. The application generates the archive and XML files and delivers them to the destination, for example, WebCenter Content. The Delete Archive parameter provides you with options to delete the archives and XML files after the application delivers the extract data to its destination. After the application delivers the output, for example, to WebCenter Content, you have the option to discard the archive data and XML files, therefore reducing storage consumption by deleting these extract archives.

You also have the flexibility to choose whether you discard all the data an extract generates, for example, use the Delete archive information and generated XML option to remove all unnecessary data. Or you can choose the Delete archive information only option to remove the archive data and retain the generated XML data. You may want to keep the XML data for reporting purposes or for future references.

How can I improve the performance of the application during integration testing or when bulk data loads run?

Contact your support representative and request them to manually gather the database table statistics for your pod. You may experience slow HCM Extract operations during certain testing phases of your implementation cycle, especially when the application tests bulk data loads at the same time. During regular operations the collection of statistics is scheduled to run weekly. However, if the data volume is high due to bulk data loads, then you should request this process to run manually.