Test Data Management

Data Management

Test data management is the process of creating realistic test data for non-production purposes such as development, testing, training or QA.
Research shows that projects are not successful due to a lack of data quality. We design test data management strategy not only to ensure greater development and testing efficiencies but helps projects to identify and correct defects early in the development process when they are cheapest and easiest to fix.

Test data preparation

Involves the identification and production of data by cloning or subsetting data from the live environment or by developing test data generation scripts and provisioning them for multiple testing environments.


We know that Data is scattered across systems and sits in different formats. In addition, different rules may be applied to data depending on its type and location.

Subset production data

We design subsetting to ensure realistic, referentially intact test data from across a distributed data landscape without added costs or administrative burden.

Mask or de-identify

We help the project in masking production data to secure sensitive data especially, client and employee information. We de-identifying confidential data to ensure a realistic look and feel to complete business objects, such as customer orders, across test systems.

Refresh test data

During the testing process, test data often diverge from the baseline, resulting in a less than optimal test environment but we recommend refreshing test data which can improve testing efficiencies. We help the projects in preparing Synthetic Data generation for testing new functionality.

Automate test data

The ability to identify data anomalies and inconsistencies during testing is essential to the overall quality of the application. The only way to truly achieve this goal is to deploy an automated capability for comparing the baseline test data against results from successive test runs.