Informatica Developer

Effective in 10.1, you can use the file name column option to return the source file name. You can configure the mapping to write the source file name to each source row.

For more information, see the Informatica 10.1 Developer Tool Guide.

Effective in version 10.1, you can import mappings that contain Netezza and Teradata objects from PowerCenter into the Developer tool and run the mappings in a native or Hadoop run-time environment.

For more information, see the Informatica 10.1 Developer Mapping Guide.

Effective in version 10.1, you can copy text from Excel to the Developer tool or from the Developer tool to Excel. Copy text from Excel to the Developer tool to provide metadata for transformations. For example, you have designed a mapping in Excel that includes all transformations, their port names, data types, and transformation logic. In the Developer tool, you can copy the fields from Excel into the ports of empty transformations. Similarly, you can copy transformation ports from the Developer tool into Excel.

Effective in Informatica 10.1, you can use the logical data object editor to edit and change metadata in logical data object Read and Write mappings. For more information, see the "Logical View of Data" chapter in the Informatica 10.1 Developer Tool Guide.

Effective in version 10.1, when you choose to create or replace the target at run time, you can define a DDL query based on which the Data Integration Service must create or replace the target table at run time. You can define a DDL query for relational and Hive targets.

You can enter placeholders in the DDL query. The Data Integration Service substitutes the placeholders with the actual values at run time. For example, if a table contains 50 columns, instead of entering all the column names in the DDL query, you can enter a placeholder.

You can enter the following placeholders in the DDL query:

You can also enter parameters in the DDL query.

For more information, see the Informatica 10.1 Developer Mapping Guide.

Effective in version 10.1, you can create a column profile on an Avro or Parquet data source in HDFS.

For more information about column profiles on Avro and Parquet data sources, see the "Column Profiles on Semi-structured Data Sources" chapter in the Informatica 10.1 Data Discovery Guide.

Effective in version 10.1, you can select a minimum number of conforming rows as conformance criteria for data domain discovery.

For more information about conformance criteria, see the "Data Domain Discovery in Informatica Developer" chapter in the Informatica 10.1 Data Discovery Guide.

Effective in version 10.1, you can exclude null values from the data set when you perform data domain discovery on a data source. When you select the minimum percentage of rows with the exclude null values option, the conformance percentage is the ratio of number of matching rows divided by the total number of rows excluding the null values in the column.

For more information about exclude null values from data domain discovery option, see the "Data Domain Discovery in Informatica Developer" chapter in the Informatica 10.1 Data Discovery Guide.

Effective in version 10.1, you can choose the Hadoop option as the run-time environment when you create or edit a column profile, data domain discovery profile, enterprise discovery profile, or scorecard. When you choose the Hadoop option, the Data Integration Service pushes the profile logic to the Blaze engine on the Hadoop cluster to run profiles.

For more information about run-time environment, see the "Data Object Profiles" chapter in the Informatica 10.1 Data Discovery Guide.