“Data is power and only those who know how to manage, structure, and harness it right could taste the expected outcomes.” ~ Kanika Vatsyayan
Test data is a highly significant part of the quality assurance process. Especially, the ever-growing pace of digitalization that bring along applications, software, and other enterprise technology with it.
Also, when test data holds so much significance in the process of managing and streamlining the software technology, wonder what extraordinary it could drive to the Quality Assurance process? Especially, when most business organizations these days have varying business goals, catering to end-user goals requires effective test data management.
Be it setting the test environments or defining the behavioral patterns related to technology, the process involves the use of very exact test data. And since a large amount of the testing team’s time is spent working on the test plan and related tasks, the unavailability of the appropriate test data often makes it very challenging to yield the necessary test coverage.
According to Kobiton, 55% of companies that are pursuing automated testing strategies cite quality improvement and 30.2% cite time to market as their main driver. And it is access to such numbers and data only that allows firms on their digital journeys to proceed in the right direction.
As a software testing service provider we are aiming to dive into all the new and innovative test practices. However, it is extremely necessary that the need for effective test data management must be recognized in order to foster efficiency and yield the expected outcomes for the future.
Unraveling The Challenge
When it comes to software testing, the process involves a lot of changes and reworks. And all these tasks usually occupy QA testers making the process very challenging. Let us quickly dive through challenges related to test data management before we jump on learning the strategies that could help improve the test data management process.
The Constant Need For Refreshed Data
The primary reason why test cycles are mostly delayed is the constant re-work that adds more information to the data. It not only adds to the cost of the software but even makes it tough to capture all the information.
And just in case, the product under development has different workgroups involved for different functionalities and integrations, the creation and refreshing of test data makes the entire process even more intricate.
As all this data needs to be created from scratch for adequate testing, the QA teams even need to focus on putting together all the data and get it stored in some kind of repository.
The Unwanted Data
Though having a repository established in your organization is a smart move, the next big challenge that affects the test process is dealing with excessive and unwanted data. This data not only takes up the storage space but makes it more complicated to filter the required data when testing. Usually, such issues occur due to improper version maintenance or excessive data archives.
Effective Strategies To Manage Huge Software Testing Data
Most organizations have to face the hassle of storing and managing test data. And thus, it becomes necessary to have the perfect management strategy that can keep the data in place minimizing any chances of risks or challenges.
However, it is the right approach to boost software testing productivity with test data management tactics that makes all the difference. From keeping the data organized to ensuring relevance in application, there are certain practices that can streamline the entire test process.
Wondering What Test Data Management Is?
Read Here: Generate & Manage Test Data with TDM (Test Data Management)
Analysis of Data
Most of the time, test data is constructed based on the test cases that need to be executed. For instance, a testing team working in a test system works on end-to-end test scenarios that must be worked for designing the test data.
But, how to accelerate test data management?
The process usually involves more than one product or works on different components of the product at the same time. Consider an application that is meant to work on cloud management with a middleware application, database application, and a workload management system in place, the test data for testing all these components would be different.
Thus, it is crucial that test data must be analyzed and based on the analysis the different test data must be generated from the existing and new data to ensure effective testing.
Mirroring The Production Setup
The concept of establishing the production setup works along with the data analysis. It needs to understand the production scenarios for what data is required to foster the production scenario. Furthermore, the data developed is used and compared with the existing data for the current test environment to ensure necessary modifications or updates using the new data.
Test Data Cleanup
For release cycles that can span over a long time, the test data might require frequent alterations just like we have talked about above in case of establishing a new production setup. In such a case, the data developed may not be immediately relevant and can add value to the test process at a later point. Thus, a definitive process must be created to work on test data cleanup to avoid any unwanted loss.
Sensitive Data
Most of the time, testing the applications is not convenient due to the massive requirements of sensitive data. For example, testing an application for a cloud-based environment requires access to real-time testing data of different products to add speed to the process.
However, working on anything that involves user privacy in a cloud-sensitive environment is a subject of concern. But whenever the process might involve replicating the user environment, the sensitive data must be guarded and here’s where the importance of TDM in software testing for businesses can be understood. And this process to shield sensitive data entirely depends on the volume of data used.
Automation
Just as automation has been adopted for running repetitive tests or the same tests with different data, automation can even be used to create test data. The process helps in exposing the errors with the data that may happen during testing. Though another way of working on such a process can be comparing the results from different data from consecutive test runs, making the comparison process automated helps add more value to the process.
Data Refresh & Central Repository
This step is one of the most significant parts of the data management process and even to work on all the steps defined above that need data setup or clean up. Maintaining a central repository allows cutting all the effort required to create the test data for various kinds of testing. This actually works by working on consecutive test cycles, where every new test case of the modified test case is made to reflect on the existing data in the repository. For any chance where data does not exist, the data can be fed to the test environment first.
When done, the data can be directed to the repository for similar test cases in the future. This will allow test teams to foster consecutive release cycles using all the data or its subsets. And the best part of working on such a strategy is the ease of eliminating any obsolete data that is generated after frequent testing. It creates space for correct data and thus reduces the cost of storage for all the unwanted data.
Besides, you can always have the advantage of revising the different versions of the repository whenever required. The availability of different versions enables you to quickly meet any goals like regression testing to learn what changes in data cause code to break.
Fetching The Verdict!
Be it any test team, the test environment holds the maximum importance in defining the outcomes of the test process. Also, every release cycle has its own new challenges involved which must be fixed to overcome unreliable and unplanned testing.
And this is why, most organizations, either working on pure-play testing or establishing a QA division into their operations are working on strategies to create more dedicated test environments. Besides, they focus on developing maintenance teams that can work on all the maintenance to create more streamlined tests and release cycles.
After all, improved software testing services are a product of smooth test data management. From creating cost-effective products to reliable production, test data management is the key to success.
Good Luck!
Need help maintaining your huge software testing data? Wondering how our experts at BugRaptors could assist you in establishing a more refined QA setup? Ask our experts!
Reach us through info@bugraptors.com
