Table of Contents

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  1. Preface
  2. Introduction to Test Data Management
  3. Test Data Manager
  4. Projects
  5. Policies
  6. Data Discovery
  7. Creating a Data Subset
  8. Performing a Data Masking Operation
  9. Data Masking Techniques and Parameters
  10. Data Generation
  11. Data Generation Techniques and Parameters
  12. Working with Test Data Warehouse
  13. Analyzing Test Data with Data Coverage
  14. Plans and Workflows
  15. Monitor
  16. Reports
  17. ilmcmd
  18. tdwcmd
  19. tdwquery
  20. Appendix A: Data Type Reference
  21. Appendix B: Data Type Reference for Test Data Warehouse
  22. Appendix C: Data Type Reference for Hadoop
  23. Appendix D: Glossary

User Guide

User Guide

Test Data Management Overview

Test Data Management Overview

Test Data Management (TDM) integrates with PowerCenter, PowerExchange®, and Informatica applications to manage nonproduction data in an organization.
With TDM, an organization can create a smaller copy of the production data and mask the sensitive data. An organization can discover the sensitive columns in the test data, and ensure that the sensitive columns are masked in the test data. An organization can also create test data that does not contain sensitive data from the production database. They can create a test data warehouse to store test data in a central location and edit or reset the data when required.
Organizations create multiple copies of application data to use for testing and development. Organizations often maintain strict controls on production systems, but data security in nonproduction systems is not as secure. An organization must maintain knowledge of the sensitive columns in the production data and ensure that sensitive data does not appear in the test environment. Development must not have to rewrite code to create test data.
Manage data discovery, data subset, data masking, and data generation in Test Data Manager.
Data discovery
Use data discovery to run sensitive field profiles to identify the columns that contain sensitive data. Use the profile results to determine which columns to mask and which data masking techniques to apply. Define data domains to identify sensitive data columns by patterns in the data or the column metadata. When you apply data masking, you can apply the same rule to multiple columns in the same data domain. You can run primary and foreign key profiles to discover potential primary key-foreign key constraints to define relationships between parent and child tables.
Data subset
Use data subset to create a small environment for testing and development. You can define the type of data that you want to include in the subset database. You might create a subset database with data based on time, function, or geographic location. For example, a time-based subset database might include recent payment transactions from all invoice data in a production system.
Data masking
Create data masking rules to apply to source columns and data domains. You can apply different masking techniques such as substitution masking, shuffle masking, key masking, and encryption. You can configure repeatable results in the masked data. You can assign multiple rules to the same column.
Data generation
Use data generation to create a testing environment that does not use data from the production database. Create data generation rules to define the type of data you want to generate. TDM generates data in a schema that you can use for testing.
Manage Data Sets
Manage data sets that you store in the test data warehouse. You can view and edit the data or reset the data to a test system from Test Data Manager. For example, you run multiple test cases, or multiple test teams work on an application. You can store the test data in the test data warehouse. When one test team completes testing, save the modified test data as another version of the original data set in the test data warehouse. Restore the required version from the test data warehouse to the test environment to run other test cases or for a different team to work with.
Create a Self-Service Portal for specific users
You can allow users who use the test data warehouse data but do not create the data, to access the data from the self-service portal. The self-service portal provides an uncluttered UI and access is limited to required tasks.
Data coverage analysis
Create data coverage tasks to analyze the data in a data set. You can visualize the data coverage across pairs of columns and use filter columns to further configure the analysis. Based on the results, you can choose to update data to ensure that you have enough data in required cells to meet the test case requirements.
To perform data subset and masking operations, you can generate and run workflows from data subset and data masking plans in Test Data Manager.
To perform data generation operations, you can generate and run data generation plans in Test Data Manager.
You can export test data to an HP ALM server from TDM. You can copy results of subset, masking, and generation operations that have flat file targets. Integrate the HP-ALM test tool with TDM to directly copy and maintain flat file results in an HP ALM server. You can then use the data to create and run test cases in HP ALM.
Configure a test data warehouse to create and work with data sets in Test Data Manager. Create a data set from any data subset, data masking, or data generation plan that you run in Test Data Manager.
Use the self-service portal for users who require limited access to TDM features.
You can perform data masking and data movement on Hadoop clusters. Use Hadoop sources to lower the cost of raw data storage and to solve large scale analytics by using the distributed computing capabilities of Hadoop. For example, when you move sensitive data into Hadoop, you can classify data for analytics, provision data for testing, or other purposes.
Use Hadoop to improve the speed of processing large volumes of structured and unstructured data. For example, you work with heterogeneous data sets and you want to normalize and correlate data sets of the size of terabytes or petabytes. The analytics results processed on Hadoop are faster and cost-effective, and you can extract the analytics results to a conventional database.
TDM includes the ilmcmd command line program. Run ilmcmd commands to perform a subset of the Test Data Manager tasks from the command line.
TDM users have roles and privileges that determine the tasks that they can perform through Test Data Manager or the ilmcmd command line program. The administrator manages roles and privileges for users from the Informatica Administrator.

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