Export, import, and copy data into a legal entity

9 minutes

This unit explains how to copy data into a legal entity, and how to import and export data in finance and operations apps.

Data import and export jobs

To create and manage data import and export jobs in finance and operations apps, you can use the Data management workspace. By default, the data import and export process creates a staging table for each entity in the target database. Staging tables let you verify, clean up, or convert data before you move it.

The following are steps to import or export data.

Create an import or export job, where you will complete the following tasks:
- Define the project category.
- Identify the entities to import or export.
- Set the data format for the job.
- Sequence the entities so that they are processed in logical groups and in an order that makes sense.
- Determine whether to use staging tables.
Validate that the source data and target data are mapped correctly.
Verify the security for your import or export job.
Run the import or export job.
Validate that the job ran as expected by reviewing the job history.
Clean up the staging tables.

Create an import or export job

A data import or export job can be run one time or as many times as needed. We recommend that you take the time to select an appropriate project category for your import or export job. Project categories can help you manage related jobs.

When you select an entity, you must select the format of the data that will be exported or imported. You can define formats by using the Data sources setup tile. A source data format is a combination of Type, File format, Row delimiter and Column delimiter.

Entities can be sequenced in a data template or in import and export jobs. When you run a job that contains more than one data entity, you must make sure that they are correctly sequenced. Primarily, you sequence entities to address any functional dependencies among entities. If entities don’t have any functional dependencies, they can be scheduled for parallel import or export.

Verify the security for your import or export job

Access to the Data management workspace can be restricted so that non-administrator users can access only specific data jobs. Access to a data job implies full access to the run history of that job and access to the staging tables. Therefore, you need to make sure that appropriate access controls are in place when you create a data job.

Use the Applicable roles menu to restrict the job to one or more security roles. Only users in those roles will have access to the job. You can also restrict a job to specific users. Securing a job by users instead of roles provides more control when multiple users are assigned to a role.

A job can be secured by roles, users, and legal entity at the same time. Data jobs are global in nature. Therefore, if a data job was created and used in a legal entity, the job will be visible in other legal entities in the system. This default behavior might be preferred in some application scenarios.

For example, an organization that imports invoices by using data entities might provide a centralized invoice processing team that is responsible for managing invoice errors for all divisions in the organization. In this scenario, it’s useful for the centralized invoice processing team to have access to invoice import jobs from all legal entities. Therefore, the default behavior meets the requirement from a legal entity perspective.

However, an organization might want to have invoice processing teams for each legal entity. In this case, a team in a legal entity should have access only to the invoice import job in its own legal entity. To meet this requirement, you can configure legal entity–based access control on the data jobs by using the Applicable legal entities menu inside the data job. After the configuration is done, users can view only jobs that are available in the legal entity that they are currently signed in to. To view jobs from another legal entity, users must switch to that legal entity.

Clean up the staging tables

You can clean up staging tables by using the Staging clean up feature in the Data management workspace. You can use the following options to select which records should be deleted from which staging table:

Entity – If only an entity is provided, all records from that entity’s staging table are deleted. Select this option to clean up all the data for the entity across all data projects and all jobs.
Job ID – If only a job ID is provided, all records for all entities in the selected job are deleted from the appropriate staging tables.
Data projects – If only a data project is selected, all records for all entities and across all jobs for the selected data project are deleted.

Watch this video to learn how to perform data export and import by using the Data management workspace:

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