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  1. Preface
  2. Part 1: Version 10.2
  3. Part 2: Version 10.1.1
  4. Part 3: Version 10.1
  5. Part 4: Version 10.0
  6. Part 5: Version 9.6.1
  7. Part 6: Version 9.6.0

Informatica Data Quality

Informatica Data Quality

This section describes new features and enhancements to Informatica Data Quality.

Accelerators

The set of Informatica accelerators has the following additions:
  • Informatica Data Quality Accelerator for Spain. Contains rules, reference tables, demonstration mappings, and demonstration data objects that solve common data quality issues in Spanish data.
  • Informatica Data Quality Accelerator for Data Discovery. Contains rules, reference tables, demonstration mappings, and demonstration data objects that you can use to perform data discovery operations.
For more information, see the
Informatica Data Quality
9.6.0
Accelerator Guide
.

Address Validation

You can configure the following advanced properties on the Address Validator transformation:
Dual Address Priority
Determines the type of address to validate. Set the property when input address records contain more than one type of valid address data.
Flexible Range Expansion
Imposes a practical limit on the number of suggested addresses that the transformation returns when there are multiple valid addresses on a street. Set the property when you set the Ranges to Expand property.
Geocode Data Type
Determines how the transformation calculates geocode data for an address. Geocodes are latitude and longitude coordinates. Set the property to return the following types of geocode data:
  • The latitude and longitude coordinates of the entrance to a building or a plot of land.
  • The latitude and longitude coordinates of the geographic center of a plot of land.
The transformation can also estimate the latitude and longitude coordinates for an address. Estimated geocodes are called interpolated geocodes.
Global Max Field Length
Determines the maximum number of characters on any line in the address. Set the property to verify that the line length in an address does not exceed the requirements of the local mail carrier.
Ranges To Expand
Determines how the transformation returns suggested addresses for a street address that does not specify a house number. Set the property to increase or decrease the range of suggested addresses for the street.
Standardize Invalid Addresses
Determines if the transformation standardizes data values in an undeliverable address. Set the property to simplify the terminology in the address record so that downstream data processes can run more efficiently.
You can configure the following address validation process property in the Administrator tool:
SendRight Report Location
The location to which address validation writes a SendRight report and any log file that relates to the creation of the report. Generate a SendRight report to verify that a set of New Zealand address records meets the certification standards of New Zealand Post.
You configure the Address Validator transformation to create a SendRight report file.
For more information, see the
Informatica
9.6.0
Developer Transformation Guide
.

Automatic Workflow Recovery

You can configure automatic recovery of aborted workflow instances due to an unexpected shutdown of the Data Integration Service process. When you configure automatic recovery, the Data Integration Service process recovers aborted workflow instances due to a service process shutdown when the service process restarts.
For more information, see the
Informatica 9.6.0 Developer Workflow Guide
.

Business Glossary

Business Glossary comprises online glossaries of business terms and policies that define important concepts within an organization. Data stewards create and publish terms that include information such as descriptions, relationships to other terms, and associated categories. Glossaries are stored in a central location for easy lookup by end-users.
Business Glossary is made up of glossaries, business terms, policies, and categories. A glossary is the high-level container that stores other glossary content. A business term defines relevant concepts within the organization, and a policy defines the business purpose that governs practises related to the term. Business terms and policies can be associated with categories, which are descriptive classifications. You can access Business Glossary through Informatica Analyst (the Analyst tool).
For more information, see the
Informatica 9.6.0 Business Glossary Guide.

Column Profile Results

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
.

Curation

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
.

Datatype Inference

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
.

Identity Index Data Persistence

You can configure a Match transformation to write the identity index data for a data source to database tables. You can configure a Match transformation to compare a data source to the identity index data in the database tables. The stored index data for one of the two data sources means that the identity match mappings take less time to run.
When you configure a Match transformation to read index tables, you control the types of record that the transformation analyzes and the types of output that the transformation generates. You can configure the transformation to analyze all the records in the data sources or a subset of the records. You can configure the transformation to write all records as output or a subset of the records.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.

Java Transformation

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
.

Lookup Transformation

If you cache the lookup source for a Lookup transformation, you can use a dynamic cache to update the lookup cache based on changes to the target. The Data Integration Service updates the cache before it passes each row to the target.
For more information, see the
Informatica 9.6.0 Developer Transformation Guide
.

Normalizer Transformation

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
.

Performance

In the Developer tool you can enable a mapping to perform the following optimizations:
  • 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 Mapping Guide
.

Profile Results Verification

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
.

Pushdown Optimization

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
.

Rule Builder

Rule Builder is an Informatica Analyst feature that converts business rule requirements to transformation logic. You save the business rule requirements in a rule specification. When you compile the rule specification, the Analyst tool creates transformations that can analyze the business data according to the requirements that you defined. The Analyst tool saves the transformations to one or more mapplets in the Model repository.
A rule specification contains one or more
IF-THEN
statements. The
IF-THEN
statements use logical operators to determine if the input data satisfies the conditions that you specify. You can use AND operators to link IF statements and verify that a data value satisfies multiple conditions concurrently. You can define statements that compare data from different inputs and test the inputs under different mathematical conditions. You can also link statements so that the output from one statement becomes the input to another.
Rule Builder represents a link between business users and the Informatica development environment. Business users can log in to the Analyst tool to create mapplets. Developer tool users add the mapplets to mappings and verify that the business data conforms to the business rules.
For more information, see the
Informatica 9.6.0 Rule Builder Guide
.

Scorecards

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
.

Sequence Generator Transformation

Effective in 9.6.0, you can 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
.


Updated September 25, 2020