The Address Validator Port Reference is written for Data Quality users who configure the Address Validator transformation to perform address parsing and validation tasks. The document describes the functionality and usage of each port and the types of information each port can contain. The Address Validator Port Reference lists the ports …
The Informatica Administrator Guide is written for Informatica domain administrators and operators. It contains information that you need to configure, manage and monitor the domain. The Administrator Guide assumes that you have basic working knowledge of the Informatica domain and services.
The Informatica Analyst Tool Guide describes how to use Informatica Analyst (the Analyst tool) to discover and define business logic and collaborate on business projects in an enterprise. It is written for business users such as analysts and data stewards who collaborate on projects within an organization. This guide assumes that you have an …
The Informatica Business Glossary API Guide is written for developers who write client applications that need to access a business glossary. It contains information you need to include the business glossary in your client application. This guide assumes you have a working knowledge of application programming interfaces.
The Informatica Application Service Guide is written for Informatica users who need to configure application services. The Informatica Application Service Guide assumes you have basic working knowledge of Informatica and details of the environment in which the application services run.
The Informatica Business Glossary Started Guide is written for data stewards, owners, stakeholders, and Glossary consumers who are responsible for creating and viewing Business Glossary content. It provides a tutorial to help first-time users learn how to use Informatica Business Glossary.
The Business Glossary Guide is written for administrators, data stewards, business owners, subject matter experts, business users, and business analysts who read and manage a business glossary. It contains information you need to look up content, create, and manage business glossaries and relate the information between glossary content. The …
The Informatica Command Reference is written for Informatica administrators and developers who manage the repositories and administer the domain and services. This guide assumes you have knowledge of the operating systems in your environment. This guide also assumes you are familiar with the interface requirements for the supporting applications.
The Informatica Content Installation Guide is written for Informatica users who are responsible for installing prebuilt rules and reference data to Informatica Data Quality or to PowerCenter®.
The Informatica Data Discovery Guide is written for Informatica Analyst and Informatica Developer users. It contains information about how you can use profiles to analyze the content, quality, and structure of data sources and perform data discovery to discover the metadata of source systems that include content and structure. Use profiles to …
The Informatica Data Quality Accelerator Guide is written for Informatica developers who import and use accelerators. Accelerators are content bundles that address common data quality problems in a country, a region, or an industry. The guide assumes that you have an understanding of data quality concepts such as standardization, parsing, …
The Data Quality for Microsoft Excel Guide is written for Excel users and data quality developers. This guide assumes that Excel users are familiar with Microsoft Excel. This guide also assumes that data quality developers are familiar with creating data quality mappings and web services.
This document contains important information about installation and known limitations for Data Quality for Microsoft Excel.
Desktop Guide
The Informatica Developer Mapping Guide contains information about how to create and use mappings and mapplets, configure dynamic mappings, export and import objects, and to enable performance tuning and pushdown optimization. The Informatica Developer Mapping Guide is written for developers who develop mappings and mapplets, such as big data, …
The Informatica Developer Tool Guide is written for big data, data services, and data quality developers. This guide describes common functionality in the Developer tool. This guide assumes that you have an understanding of flat file and relational database concepts, and the database engines in your environment.
The Informatica Developer Transformation Guide contains information about transformation functionality in the Developer tool. It is written for data quality, big data, and data services developers. This guide assumes that you have an understanding of data quality concepts, flat file and relational database concepts, and the database engines in your …
The Informatica Developer Workflow Guide is written for developers and administrators who are responsible for creating and running workflows. This guide assumes that you have an understanding of flat file and relational database concepts, the database engines in your environment, and data quality concepts. This guide also assumes that you are …
The Informatica Exception Management Guide describes how to use Exception Managment in the Analyst tool. Exception Management is an Analyst tool feature that you can use to view and update data quality exception records in a Human task. Exceptions are records that might contain bad data or duplicate data. Use Exception Management to resolve data …
The Data Quality Getting Started Guide is written for data quality developers and analysts. It provides tutorials to help first-time users learn how to use Informatica Developer and Informatica Analyst. This guide assumes that you have an understanding of data quality concepts, flat file and relational database concepts, and the database engines in your environment.
The Informatica Installation and Configuration Guide is written for the system administrator who is responsible for installing the Informatica product. This guide assumes you have knowledge of operating systems, relational database concepts, and the database engines, flat files, or mainframe systems in your environment. This guide also assumes you …
The Informatica Message Reference is written for all Informatica users. This guide contains troubleshooting information for all aspects of data warehouse development, including source analysis, transformation development, mapping development, and running sessions. This guide assumes you have knowledge about your operating systems, relational …
The Informatica Performance Tuning Guide is written for administrators and developers who are interested in improving performance. This guide assumes you have knowledge of the operating systems, networks, client tools, relational database concepts, and flat files in your environment. For more information about database performance tuning not …
The Informatica Profile Guide is written for Informatica Analyst and Informatica Developer users. It contains information about how you can use profiles to analyze the content and structure of data. Use column profiles to determine the characteristics of columns, such as value frequency, percentages, and patterns, in a data source.
The Informatica Profiling Getting Started Guide is written for data quality and data services developers and analysts. It provides a tutorial to help first-time users learn how to use Informatica Developer and Informatica Analyst. This guide assumes that you have an understanding of data quality concepts, flat file and relational database concepts, …
The Informatica Reference Data Guide includes information about the reference data objects and files that you can use in Informatica Developer and Informatica Analyst. It is written for data analysts, data stewards, and others who use reference data to verify and enhance the accuracy and usability of organization data.
This document contains important information about fixed limitations and emergency bug fixes for Informatica 10.2 HotFix 1.
A rule specification represents the data requirements of a business rule in logical form. You define a rule specification in the Design workspace of Informatica Analyst. You generate one or more mapplets from the rule specification that you define. An Informatica Developer user can add the mapplets to a mapping and verify that a data set …
The Informatica Security Guide contains information about security in the Informatica domain. It contains information that you need to manage security for the Informatica domain and the Informatica clients that connect to the domain. This book assumes that you have knowledge of the Informatica domain and the Informatica Administrator. It also …
The Informatica Developer Transformation Language Reference is written for the developers who are responsible for building mappings. The Informatica Developer Transformation Language Reference assumes you have knowledge of SQL, relational database concepts, and the interface requirements for your supporting applications.
The upgrade guide is written for the system administrator who is responsible for upgrading the Informatica product. This guide assumes that you have knowledge of operating systems, relational database concepts, and the database engines, flat files, or mainframe systems in your environment. This guide also assumes that you are familiar with the …
PowerCenter® users can work with mappings and reference data objects that they import from a Data Quality environment. The Informatica Data Quality Integration for PowerCenter User Guide is written for the PowerCenter users who run data quality mappings and manage the associated reference data objects.
The Informatica Web Services Guide is written for data quality and data services developers. This guide assumes that you have an understanding of web services concepts.
When you run an enterprise discovery profile in Informatica Developer, you can discover column profile statistics, data domains, primary keys, and foreign keys in a large number of data sources. A large number of keys and relationships might be inferred. You can approve, reject, or reset the inferred data domains, primary keys, or foreign keys. This article describes how you can configure the auto curation parameters to infer primary key and foreign key relationships without manual intervention. The auto curation parameters are user-defined custom attributes that you can configure to identify the data relationships based on certain conditions.
You can configure an Oracle connection to connect to Oracle Autonomous Data Warehouse Cloud (Oracle ADWC) from Informatica® Developer or PowerCenter®. This article describes how to configure connectivity to Oracle ADWC.
You can configure an Oracle connection to connect to Oracle Database Cloud Service from Informatica® Developer or PowerCenter®. This article describes how to configure connectivity to Oracle Database Cloud Service.
To identify data quality issues in multiple data sources, you can create an enterprise discovery profile, or you can create a column profile on a logical data object. This article describes how to create and run a column profile on the logical data object in Informatica Developer to identify data quality issues, such as null values, inferred data types, and inferred data patterns.
A parameter file is an .xml file that lists user-defined parameters and their assigned values. Parameter files provide the flexibility to change parameter values each time that you run a mapping or a workflow. Generate a parameter file based on a mapping or workflow using the Developer tool or the command line. Edit the contents of the file to create unique parameter files that you can use for different runs of the same mapping or workflow. This article provides a description of the elements in a parameter file as well as the steps to generate and edit a parameter file.
You can discover data on Hadoop by creating and running profiles on the data in Informatica Developer. Running a profile on any data source in the enterprise gives you a good understanding of the strengths and weaknesses of its data and metadata. A profile determines the characteristics of columns in a data source, such as value frequencies, unique values, null values, patterns, and statistics. This article describes how to create column profiles for Avro and Parquet data sources in the Developer tool.
You can use Informatica Developer to read data from Lightweight Directory Access Protocol (LDAP) directory servers. You can create column profiles on the LDAP data sources and view the profile results to find the content, quality, and structure of the data sources. This article is written for database administrators and developers and assumes that you have basic knowledge of LDAP and Informatica Data Quality product.
You can add, edit, or delete filters in a profile. A filter determines the rows that the profile reads at run time. The profile does not process rows that do not meet the filter criteria. When you create a filter for a profile or scorecard, the profile or scorecard runs on the filtered data. This article describes how to create filters for a profile and apply the filters in the scorecard that you create from the profile results.
When you analyze data in data sources, you might come across data that do not fall within an expected range of values or patterns, such as employee names that do not fall within an expected set of patterns or a Social Security Number that appears multiple times in an Employee database. To identify these anomalies, you can create a column profile on the data source and detect outliers in the profile results. This article describes how a data analyst can use outliers in a column profile results to identify anomalies in data patterns, values, and frequency in the data source.
In the Developer tool, you can develop a dynamic mapping that handles metadata changes in relational sources at run time. This article describes the steps to create a dynamic mapping for relational tables that can have metadata changes and to run the mapping with metadata changes. This article assumes that you are familiar with mapping and dynamic mapping concepts and know how to develop and run a mapping.
In the Developer tool, you can develop a dynamic mapping that reuses the same mapping logic for different sources and targets. This article describes the steps to create a dynamic mapping with a mapping logic that you can run against different sources and write to different targets. This article assumes that you are familiar with mappings and dynamic mappings and know how to develop and run a mapping.
Domain and application services ports can either be static ports or dynamic ports. The Informatica domain and domain components are assigned to static ports. Certain application services are also assigned to static ports while others run on dynamic ports.
The system resource guidelines for profiling and discovery include resource recommendations for the Profiling Service Module, the Data Integration Service, profiling warehouse, and hardware settings for different profile types. This article describes the system resource and performance tuning guidelines for profiling and discovery.
When you run a profile or scorecard, the profile and scorecard results are saved in the profiling warehouse. You can delete these results from the profiling warehouse. This article discusses how to purge the profile results and scorecard results from the profiling warehouse.
You can run a mapping that reads NVARCHAR and NCHAR data from SAP tables with a JDBC connection. Before you can run the mapping, you must configure properties for the Data Integration Service that runs the mapping in Informatica Administrator and configure properties for Informatica Developer (the Developer tool) in the developerCore.ini file. This article describes the configuration tasks that you must perform before you run the mapping.
To improve Developer tool mapping performance, use best practices when you configure mappings and apply relational pushdown optimization. Relational pushdown optimization causes the Data Integration Service to push transformation logic to a database. Pushdown optimization improves mapping performance as the source database can process transformation logic faster than the Data Integration Service. The Data Integration Service also reads less data from the source.
When you run a profile on JSON and XML data sources, Informatica Developer treats the files as flat files. This article describes how you can create column profiles on flat file data sources that are in JSON or XML format, and view the profile results for data analysis and development.
Informatica provides a list of supported upgrade paths for users who want to upgrade their Informatica product. This article describes the supported upgrade paths to upgrade to Informatica 10.1.1 and 10.1.1 hotfix releases.
Informatica 10.2 HotFix 2 contains various improvements and enhancements to the Informatica domain. Informatica provides a list of supported upgrade paths for users who want to upgrade their product. This article describes the supported upgrade paths to upgrade to Informatica 10.2 HotFix 2.
Lightweight Directory Access Protocol (LDAP) is a software protocol for accessing users and resources on a network. You can configure an Informatica domain to use LDAP to authenticate Informatica application client users.
You can synchronize the changes in the external data source to the data object in the Model Repository after you create and run a profile on the data object. You can also synchronize the curated results of an enterprise discovery profile after you migrate the profile from version 9.5 to a later release. This article discusses the Synchronize and Synchronize Enterprise Discovery Profile options and explains how to use the options based on your requirement.
Informatica Blaze engine is an Informatica proprietary engine for distributed processing on Hadoop. You can run profiles and scorecards on the Blaze engine. This article discusses how you can use the Blaze engine to run profiles and scorecards in Informatica Developer and Informatica Analyst.
You can choose to run a profile on all the rows in a data object, first N number of rows, or a random sample of data in the data object. This article discusses the random sampling options in profiling and how to use the options based on your requirement.
Updated September 2018
