The Role of Test Data Management in Accelerating Software Delivery and Reducing Risk
Test data management (TDM) is crucial for establishing a high-level automation process in software development. Unfortunately, many professionals are unfamiliar with TDM and don’t know why it’s important.
The software development industry is going through a rapid change and organizations working in this industry need to evolve accordingly. For instance, they need to use new tools and techniques such as Agile, DevOps, etc. Other than this, one additional tool they need is test automation. Since test automation needs data to work, that’s where TDM comes in.
Test Data Management: What is it?
Test data management is the process of acquiring and implementing the test data required for test automation processes with limited human intervention. TDM ensures that the test data is always available and its quality up to the mark.
Why TDM Matters?
Forward-thinking companies understand that releasing new software updates every month or even week isn’t enough. They need to deploy several times every single day to remain competitive in the industry. And how do they do it without compromising the quality of each software version? The answer is automation.
Since manual testing is seldom effective, a good test automation strategy is what companies need to building powerful and reliable apps at a fast pace. That’s where TDM helps.
The following are a few ways TDM helps in speeding software delivery and reducing risk:
1. Test data redundancy prevention
A lot of times, software developers create multiple copies of their code to help with the testing. Due to so many copies of similar size and nature, product owners get easily confused in understanding which copies are useful and which aren’t. TDM can help with this situation and solve not just one but two problems.
The first problem that TDM solves is increased storage costs. TDM limits redundant data which in turn limits data storage requirements.
The second problem TDM solves is data management inefficiency. Since TDM helps in identifying redundant or duplicate test data, it improves data governance and management.
2. Data bloating prevention
When company data grows, storage and maintenance costs rise. Since keeping only healthy data is important, it can be a good idea to generate and keep static test data. When this static test data has served its purpose, it can be archived. This can be easily taken care of with the use of TDM. In fact, TDM can also help with routine test data cleanup activities.
3. Smart QA analysis
A smart way to conduct data testing is cognitive QA as it allows for automation that uses quality data. It also makes it easy to align business test functions to desired outcomes. TDM makes it easy to apply QA analysis that ensures quick delivery of quality code.
4. Reduced costs irrespective of bug detection timing
When developers identify bugs in the early stages of SDLC, it’s easy to fix them and the cost impact is also less. However, when bugs are encountered in the later stages of SDLC, then the costs of fixing them can be huge.
When unexpected bugs crop up towards the end of SDLC, it can take a lot of time to duplicate the product code. If there is an existing TDM strategy, then the time in duplicating production data can be avoided. This is because the required data will be already there for fixing the bugs no matter which stage of the SDLC developers are at.
How does test data management work?
TDM involves different techniques, of which the main ones are:
- Test data exploration:A company’s data can be stored in different formats and different systems. Certain teams have to collect appropriate data from these sources based on test cases and requirements. A manual approach to this task can be highly time-consuming and counter-productive. A proper TDM tool helps here to identify the right data.
- Test data reusability:To make data processing efficient, data reusability is critical. For this technique, TDM sorts the existing data that can be used in other test cases. The data is then transferred to central archives. The data can be then easily given to teams as per their requirements. In other words, existing data can be reused many times for testing.
- Test data validation:Data collected for testing must be validated so that it complies with data privacy and security regulations. With TDM, data from production databases is validated while sensitive data is masked.
As we can reach the end of this post, it’s clear that TDM plays an important role in teams that want fast results in IT deliveries. If you are planning to go ahead with TDM, be careful and take your time. If the execution is right, you can create a strong testing foundation in your teams.