Summary

Our client, a major European Multi Play operator, was experiencing problems upgrading its IT application landscape as well as with deploying new solutions due to lack of a robust testing infrastructure. A lack of testing methodology and absence of reliable synthetic data meant that the their IT infrastructure was at risk whenever new system changes were introduced. As a result, the client organization spent unnecessary time and effort in conducting end-to-end testing efforts even for minor upgrades to ensure that bugs were weeded out before sending the changes to production.

DigitalSkunks’ leveraged it’s proprietary en-Simulate software robot as part of an overall synthetic test data management strategy. en-Simulate provided a 100% coverage of all of client’s IT application and automated the testing process thus ensuring that testing was error-free and done in the fraction of the time it took originally. This was way before bots became Bots!

Background

The client faced challenges in its testing process due to lack of test data management.

They were looking for an optimized, effective and efficient Test Data Management Solution for one of their key IT initiative that was extremely fast-paced and involved solution deployment over 14 different, but interrelated, systems hosted over heterogeneous technology platforms and networks.

Challenge

The key challenges listed below severely impacted our client’s ability to respond to its competitive environment as it prevented it from scaling its critical IT infrastructure.

• Poor test data quality leading to bugs being introduced into test environments and subsequently into production.
• Need for an extensive end-to-end regression testing to validate business function every time the system underwent a change or when a new component or system was introduced in the application landscape
• Management of concurrent data requirements in multiple test environments.
• Ensuring appropriate data was available in all applications in the test environment
• Ensuring data privacy and preventing exposure of critical and sensitive data.

Solution

• DigitalSkunks developed a comprehensive test data management strategy for the ongoing management of test data that kept pace with the growth and changes in various applications.
• Our robots kept generating usable data inline with test strategy with uniquely combined elements of data that required masking and subsetting within the defined synthetic data generation rules
• The strategy required continuously producing fresh synthetic data based on specific rules set and processes.
• Our test data strategy identified sensitive data that then was anonymized across the enterprise to enable data protection compliance
• en-Simulate allowed the client to successfully create and manage data that was both fit-for-purpose while maintaining a high level of quality at all times thereby significantly improving testing efficiency.
• en-Simulate ’s on-demand data generation capability enabled testing cohorts to meet the agile needs of the project.
• Robotic Automation de-risked production by using a small but enhanced data set existing in production environment, without the sensitive content
• Overall strategy designed appropriate process for data extraction and data loading while maintaining federated relations across multiple applications.
• We managed reference data as well streamlined data provisioning process to ensure appropriate data quality in test environment.
• Test data and test scenarios were defined traceability and dependencies were ensured
• All test data assets were reused and data usage was tracked
• en-Simulate ‘s output was periodically reviewed and analyzed.

Outcome

• en-Simulate was able to eliminate critical delays due to availability/provisioning of test data thus, shortening test cycles and resolving issues earlier and more cost-effectively in the software and project lifecycle.
• The project resulted in 99% test coverage for all test scenarios
• As a result of the project client’s IT team was able to complete upgrades and changes in the systems in time as any delays due to unavailable or missing data was completely eliminated.