Abstract: A method of generating a test database from a deployed database by “sanitizing”, or removing sensitive data, is employed for recreating problem scenarios from a customer site, verifying compatibility of customer data with database version updates, and for performance testing using actual, rather than generated, database structures. In database management operations, in can be beneficial to use data generated from actual operational scenarios rather than artificially generated data created from a test pattern. Data generated from actual operation, such has at a customer site, assures compatibility with the relation patterns and record volumes employed by the customer (user). However, databases often contain sensitive information that would be inappropriate, illegal, or vulnerable in a testing environment. Accordingly, the generated test database overwrites sensitive data values with benign, or generic values while preserving the structure and relations of the data stored.

Abstract: A method of generating a test database from a deployed database by “sanitizing”, or removing sensitive data, is employed for recreating problem scenarios from a customer site, verifying compatibility of customer data with database version updates, and for performance testing using actual, rather than generated, database structures. In database management operations, in can be beneficial to use data generated from actual operational scenarios rather than artificially generated data created from a test pattern. Data generated from actual operation, such has at a customer site, assures compatibility with the relation patterns and record volumes employed by the customer (user). However, databases often contain sensitive information that would be inappropriate, illegal, or vulnerable in a testing environment. Accordingly, the generated test database overwrites sensitive data values with benign, or generic values while preserving the structure and relations of the data stored.

Abstract: A method of generating a test database from a deployed database by “sanitizing”, or removing sensitive data, is employed for recreating problem scenarios from a customer site, verifying compatibility of customer data with database version updates, and for performance testing using actual, rather than generated, database structures. In database management operations, in can be beneficial to use data generated from actual operational scenarios rather than artificially generated data created from a test pattern. Data generated from actual operation, such has at a customer site, assures compatibility with the relation patterns and record volumes employed by the customer (user). However, databases often contain sensitive information that would be inappropriate, illegal, or vulnerable in a testing environment. Accordingly, the generated test database overwrites sensitive data values with benign, or generic values while preserving the structure and relations of the data stored.

Abstract: A method of generating a test database from a deployed database by “sanitizing”, or removing sensitive data, is employed for recreating problem scenarios from a customer site, verifying compatibility of customer data with database version updates, and for performance testing using actual, rather than generated, database structures. In database management operations, in can be beneficial to use data generated from actual operational scenarios rather than artificially generated data created from a test pattern. Data generated from actual operation, such has at a customer site, assures compatibility with the relation patterns and record volumes employed by the customer (user). However, databases often contain sensitive information that would be inappropriate, illegal, or vulnerable in a testing environment. Accordingly, the generated test database overwrites sensitive data values with benign, or generic values while preserving the structure and relations of the data stored.