The Azure Data Lake Storage Gen2 V2 and Amazon S3 V2 resources include the following enhancements:

You can include or remove source folders or files for metadata extraction using filters.
You can exclude file types such as CSV, JSON, Parquet, or Avro from partition file detection during metadata scan.
You can view the following data profiling asset enrichments for the resources:
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The Amazon Redshift resource includes the following enhancements:

You can configure the resource to include or exclude tables and views from a profile run using the Data Profile Filter.
You can configure the resource to retain the column similarity results from the previous scan in the next resource scan results using the Cumulative filter.

You can configure miscellaneous agent options for resources, such as Oracle, Sybase, JDBC, Hive, Qlik Sense, QlikView, and Teradata.

You can configure an AWS Glue resource to extract metadata using a proxy server.

The ADLS Gen 2 V2, Azure Blob, and File System resources support unique key inference.

You can export the following assets from the Axon resource for Axon glossaries in the Overview tab:

Related Glossary Assets
Related Logical Assets
Classified Assets
Related Technical Assets

You can configure a Qlik Sense resource to filter the required streams created in the Qlik Sense source system to read or publish applications, sheets, and stories.

The Snowflake Advanced Scanner relational resource type supports unique key inference.

For more information, see the

Informatica® Catalog Administrator Guide

.

When you export system attributes for assets with profiling data for resources, such as Amazon S3, Oracle, HDFS, and Snowflake, the exported CSV file includes the

Rows covered by profiling

column.

You can use the Allow Filtering option to filter the PowerCenter resource assets based on the folder name in the Enterprise Data Catalog tool.

For more information, see the

Informatica® Enterprise Data Catalog User Guide

.