In 2019, Hawaiian Airlines faced customer ire due to a glitch in their reservation system. Instead of charging the customers in miles, the airlines billed them hundreds of thousands of dollars on their credit cards. A situation that proper testing might have helped avoid.
In a market where success depends on quick releases of innovative products, failed tests are a significant business problem. According to studies, failed tests cost enterprises USD 61 billion annually by wasting 620 million developer hours in debugging software failures. In addition, it’s estimated that there is a hidden cost of data management that could be as much total product development budgets. Testing success relies heavily on quality test data, yet organizations face many challenges when it comes to creating test data sets.
Why is test data availability such a challenge?
Some of the key challenges around test data include:
- Product quality: Applications tested against generic data are unreliable and will have issues in production. This could lead to significant losses, reputational damage, and even compliance issues. Using production data is not a viable option either due to security concerns.
Quality test data in right quantity enhances the test coverage. Number of test cases not executed due to test data unavailability increases when all possible combination of data elements does not exist in lower environments. This leads to poor quality of the product and eventually results in production defects.
- Risk of a data breach: The presence of sensitive data in testing environments is a big cause for concern. Especially in highly regulated industries such as BFSI, it could create non-compliance and security issues.
- Unavailability of test data in the test environments: To run multiple tests in a given environment, testing teams need large volumes of data as every test needs a fresh set of data. Without a holistic solution to create synthetic test data, testers, dependent on the development team or production environments, often run out of it. In addition, without self-service provisioning, there are heavy upstream data dependencies that require significant coordination efforts and time. This unavailability of timely test data leads to costly delays in the testing process and impacts the product’s time to market.
- Overloaded test environments: Is there a way to overcome these challenges and make test data available in the blink of an eye? Is there a way to meet increased data demand at every testing stage? Is it possible to have data available multiple times in multiple environments with self-service provisioning? The answer is yes!
Test data management (TDM) – a critical process in the testing lifecycle
Companies need a streamlined way to create non-production data sets that reliably mimic production data for rigorous testing. Test data management helps companies generate quality test data with minimal effort. This leads to faster testing and improved product quality. Most importantly, TDM protects sensitive and personally identifiable information by data masking, minimizing the risk of data breaches.
In the next blog, we’ll discuss how TDM ensures a smooth testing process with better test coverage across multiple environments and scenarios.