The July 2025 release of Data Integration includes the following new features and enhancements.
Watch the What's New video to learn about new features and enhancements in the July 2025 release.
Creating connections when your organization uses a secrets manager
When your organization uses an external secrets manager like AWS Secrets Manager or Azure Key Vault, you can create and view connections when you create or edit a mapping or task. You can also configure the connections to retrieve sensitive credentials from the secrets manager.
Note: Effective in the July 2025 release, this functionality is available for private preview. Preview functionality is supported for evaluation purposes but is unwarranted and is not supported in production environments or any environment that you plan to push to production. Informatica intends to include the preview functionality in an upcoming release for production use, but might choose not to in accordance with changing market or technical circumstances. For more information, contact Informatica Global Customer Support.
For more information about creating connections, see Data Integration Connections.
Custom row delimiters
You can configure custom row delimiters in Source and Lookup transformations.
For more information, see Transformations
Field order for flat file targets created at run time
When you create a flat file target at run time, you can configure the target field order. When you run the task, Data Integration writes fields to the target in the order that you specify.
For more information about configuring target fields, see Transformations.
Hierarchical mappers
This release includes the following enhancements for hierarchical mappers:
•When you use a data service as the source for a hierarchical mapper, you can select Input in Native format to provide an industry-standard message in its native format as input to the hierarchical mapper. When this option isn't selected, you need to provide industry-standard messages in XML format.
•When you configure statements in a hierarchical mapper, additional validation rules take effect to ensure that the hierarchical mapper runs successfully.
•When you use an intelligent structure model as the source for a hierarchical mapper and you preview the hierarchical mapper, a validation rule takes effect to ensure that the input file is the same file type as the sample file used to create the intelligent structure model.
For example, if you create an intelligent structure model using a CSV file as the sample file, you need to use a CSV file as the input file to preview the hierarchical mapper.
•When you edit statements in a hierarchical mapper, you can select and delete multiple statements at the same time.
•You can use the h2h resource to get metadata about a hierarchical mapper. Use a GET request with the following URI:
For more information about hierarchical mappers, see Components. For more information about the REST API, see REST API Reference.
Intelligent structure models
This release includes the following enhancements for intelligent structure models:
•You can parse PDF files when you create an intelligent structure model using the custom AI engine.
•You can parse image files when you create an intelligent structure model using the CLAIRE engine.
For more information, see Components.
Joining database source objects
When you create a custom or advanced relationship to join objects in a Source transformation with an Oracle or SQL Server connection, you can join objects from different schemas.
For more information, see Transformations.
Mapping task details
If a Target transformation uses update or upsert as the target operation, the Task Details page for the mapping task displays the update columns. Previously, you needed to edit the mapping task to view the update columns.
For more information, see Tasks.
Object names in Target transformations
You can define a mapping that includes different target connections when the only difference in the object names is the case. For example, you can define a Target transformation to use an Oracle connection with the object name Sample_Table, and another Target transformation to use a Snowflake connection with the object name sample_table. Previously, the object names could only be the same if they used the same case.
For more information, see Transformations.
Schema inference from local file
When you use a flat file connection in a Source, Lookup, or Target transformation, you can use a file on your local machine to generate field metadata. You can generate field metadata from a local file for single object and command sources and for single object targets and lookups.
For more information, see Transformations.
Source control
When you undo the checkout of a source-controlled asset, you can select a different connection or runtime environment to use for the asset.
For more information, see Asset Management.
Special characters in field names
You can configure a mapping to preserve some special characters in the source and target field names. When the mapping preserves special characters, the source and target field names can include any character except the following characters: . + - = ~ ` ! $ % ^ & * ( ) [ ] { } ' \ " ; : / ? , < > | \t \r \n
The mapping replaces the listed characters with an underscore (_). Previously, the mapping replaced all characters except alphanumeric characters and underscores.
For more information, see Mappings.
Taskflows
Taskflows use TLS version 1.3 as the protocol to encrypt communications between the clients and servers on the Informatica Cloud Server. It ensures confidentiality and integrity of the data that is transmitted across a connection. TLS version 1.3 offers a faster TLS handshake and secure cipher suites.