Enterprise Data Catalog
Read this section to learn what's changed for Enterprise Data Catalog in version 10.5.
Amazon S3 Resource
Effective in version 10.5, the Amazon S3 resource includes the following enhancements in the General tab:
- Metadata extraction
- You can configure the Amazon S3 resource to extract metadata from an Amazon S3 compatible storage such as Scality RING.
- Support for temporary session token
- You can configure the Amazon S3 resource to connect and extract metadata from an Amazon S3 data source by using a temporary session token.
Previously, the enhancements were available as JVM options in the Amazon S3 resource.
For more information, see the Informatica® 10.5 Enterprise Data Catalog Scanner Configuration Guide.
Business Term Propagation
Effective in version 10.5, Enterprise Data Catalog infers and associates a business term with an asset based on enhanced name match condition. The name match condition is based on the business term association results to provide improved inference and association of business terms.
Custom Resources
Effective in version 10.5, you can run a custom resource that has the Run Script option enabled on the Informatica domain.
To run more than one custom resource on the Informatica domain simultaneously, you must configure the LdmCustomOptions.orchestration.oop.max.concurrent.jobs custom option in the Catalog Administrator.
Default Lineage and Impact Diagram View
Effective in version 10.5, the compact view of the lineage and impact diagram is the default view.
Enterprise Data Catalog Authentication
Effective in version 10.5, Enterprise Data Catalog uses mTLS in place of Kerberos for improved security.
Informatica Similarity Discovery Resource
Effective in version 10.5, the Informatica Similarity Discovery resource includes the following changes:
- Create Informatica Similarity Discovery resource
- You can create the Informatica Similarity Discovery resource from the Resource tab under the Informatica Platform resource group. When you run the resource, the scanner discovers similar columns based on column name, column data pattern, unique values in the resource. Previously, the Informatica Similarity Discovery was available as a system resource.
- Persist computed information in PostgreSQL database
- Enterprise Data Catalog persists the computed information about similar columns, column patterns, and unique values in PostgreSQL database. Previously, Enterprise Data Catalog persisted the computed information about similar columns in Apache Hbase.
- Discover similar columns
- Enterprise Data Catalog discovers similar columns based on column name, column data pattern, and unique values in the resource. Previously, an internal system job discovered similar columns based on column name, column data pattern, unique values, and value frequency in the resource.
Reference Resources
Effective in version 10.5, the reference resources include the following changes:
- Reference resource objects
- Enterprise Data Catalog extracts reference resource objects such as data sources, data sets, and data elements.
- Reference resource name
- The reference resource name is changed from <resource name>_<Provider ID>_<Connection name> to <resource name>$$<Provider ID>$$<Connection name>.
- Connection name
- Enterprise Data Catalog supports special characters in the reference resource connection name.
Search Tabs Replaced with Search Prefilters
Effective in version 10.5, you can apply search prefilters to quickly find assets that match predefined search criteria.
Previously, search tabs were available in the Search Results page that enabled you to find assets matching a set search criteria.
For more information, see the "Customize Search" chapter in the Informatica 10.5 Enterprise Data Catalog User Guide.
Note: If you upgrade from an earlier version, the upgrade process converts the customized search tabs into search prefilters.
Terminology Changes in Documentation
Effective in version 10.5, the Enterprise Data Catalog documentation uses the following terms to refer to existing and embedded clusters:
- •Internal cluster in place of an embedded cluster.
- •External cluster in place of an existing cluster.