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  1. Version 10.1
  2. Version 10.0
  3. Version 9.6.1
  4. Version 9.6.0

Informatica Data Services

This section describes new features and enhancements to Informatica Data Services.
The column profile results include the sum of all values in columns with a numeric datatype.
For more information, see the
Informatica Data Explorer 9.6.0 Data Discovery Guide
.
Use the TOTAL_SUM column in the following relational database views to access the profiling warehouse for information about the sum of values in numeric columns:
  • IDPV_COL_PROFILE_RESULTS
  • IDPV_PROFILE_RESULTS_TRENDING
For more information, see the
Informatica 9.6.0 Database View Reference
.
You can curate inferred profile results in both Analyst and Developer tools. Curation is the process of validating and managing discovered metadata of a data source so that the metadata is fit for use and reporting. You can approve, reject, and restore datatypes. You can also approve, reject, and restore data domains, primary keys, and foreign keys. You can hide or show rows containing rejected datatypes or data domains. You can exclude approved datatypes, data domains, and primary keys from column profile inference and data domain discovery inference when yo run the profile again.
For more information, see the
Informatica Data Explorer 9.6.0 Data Discovery Guide
.
Use the following relational database views to access profiling warehouse for information about curated profile results:
  • IDPV_CURATED_DATATYPES
  • IDPV_CURATED_DATADOMAINS
  • IDPV_CURATED_PRIMARYKEYS
  • IDPV_CURATED_FOREIGNKEYS
For more information, see the
Informatica 9.6.0 Database View Reference
.
You can infer multiple datatypes that match the inference criteria when you run a column profile. You can drill down based on a column datatype in column profile results.
For more information, see the
Informatica Data Explorer 9.6.0 Data Discovery Guide
.
Use the following relational database views to access profiling warehouse for information on inferred datatypes:
  • IDPV_DATATYPES_INF_RESULTS
  • IDPV_DATATYPE_FREQ_TRENDING
For more information, see the
Informatica 9.6.0 Database View Reference
.
The Data Masking transformation has the following new features in this release:
  • The Data Masking transformation is supported on Hadoop clusters. You can run the transformation in a Hive environment.
  • Tokenization is a masking technique in which you can provide JAR files with your own algorithm or logic to mask string data.
  • You can use the Phone masking technique to mask fields with numeric integer and numeric bigint datatypes.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.
In a Java transformation, you can configure an input port as a partition key, a sort key, and assign a sort direction. The Partition key and Sort key are valid when you process the transformation in a mapping that runs in a Hive environment.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.
The Normalizer transformation is an active transformation that transforms one source row into multiple output rows. When a Normalizer transformation receives a row that contains repeated fields, it generates an output row for each instance of the repeated data.
Use the Normalizer transformation when you want to organize repeated data from a relational or flat file source before you load the data to a target.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.
In the Developer tool you can enable a mapping to perform the following optimizations:
  • Push a custom SQL query to a relational data object.
  • Push operations such as Union, Union All, Intersect, Intersect All, Minus, Minus All, and Distinct to a relational data object.
  • Perform early selection and push queries that contain the SQL keyword LIMIT to a relational data object.
  • Push a Union transformation to a relational data object.
  • Push Filter, Expression, Union, Sorter, and Aggregator transformations to a Hive relational object.
For more information, see the
Informatica 9.6.0 Developer User Guide, Informatica 9.6.0 SQL Data Service Guide, and Informatica 9.6.0 Mapping Guide
.
You can verify multiple inferred primary key and functional dependency results for a single data object in the Developer tool. When you verify the profile results, the Developer tool runs the profile on all rows of the source data. You can also verify multiple data object relationships and data domains in the enterprise discovery results.
For more information, see the
Informatica Data Explorer 9.6.0 Data Discovery Guide
.
The Data Integration Service can push expression, aggregator, operator, union, sorter, and filter functions to Greenplum sources when the connection type is ODBC.
For more information, see the
Informatica 9.6.0 Mapping Guide
.
The Data Integration Service can push transformation logic to SAP HANA sources when the connection type is ODBC.
For more information, see the
Informatica 9.6.0 Mapping Guide
.
The Data Integration Service can push transformation logic to Teradata sources when the connection type is ODBC.
For more information, see the
Informatica 9.6.0 Mapping Guide
.
The REST Web Service Consumer transformation consumes REST web services in a mapping. The transformation can use GET, PUT, POST, and DELETE HTTP operations.
You can create a REST Web Service Consumer transformation from a Schema object or add elements to an empty transformation.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.
You can export scorecard results to a Microsoft Excel file. The exported file contains scorecard summary, trend charts, rows that are not valid, and scorecard properties.
For more information, see the
Informatica Data Explorer 9.6.0 Data Discovery Guide
.
You can now use the Sequence Generator transformation to add a sequence of values to your mappings.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.
You can use the SQL transformation to invoke stored procedures from a relational database. You can create the SQL transformation in the Developer tool by importing a stored procedure. The Developer tool adds the ports and the stored procedure call. You can manually add more stored procedure calls in the SQL transformation. Return zero rows, one row, or result sets from the stored procedure.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.
You can query a deployed SQL data service with Tableau through the Informatica Data Services ODBC driver.
For more information, see the
Informatica 9.6.0 Data Services Guide
.
The Web Service Consumer transformation has the following new features in this release:
  • The external web service provider can authenticate the Integration Service using NTLMv2.
  • In a Web Service Consumer transformation, you can use WSDL with one-way message pattern.
    For more information, see the
    Informatica 9.6.0 Developer Transformation Guide
    .


Updated April 09, 2019