Software testing types, tools, and techniques are so on the pinnacle of everyone’s priorities. However, not all the remarkable things are your priorities. Often concepts like test data are vividly ignored despite being an essential part of testing. It is quite strange to see how software testing prevails due to a carefully prepared data case and still receives absolute less attention.
For the record, several organizations are still so reluctant to accept the need of the hour. And they superficially force the employees to stick to the tiring traditional techniques of test data management.
Well, an ideal data set can’t be random; it has to be specific to find out errors promptly. You can’t use anything but relative, realistic and representative data. The following blog will bring the definitions, concepts, and benefits of test data and test data management into the brightest limelight ever. So, tune in.
What is Test data?
The data specially created for test practices is the test data. It is that input used in the software for testing to examine and compare the output as opposed to the expected results.
Let’s look at a few famous examples, such as the health industry and the banking industry. The data from both sectors are pretty confidential and strictly, not for testing the software. Anyhow a duplicate or a dummy is still an option; that’s where the test data comes in.
There are many ways to develop such data like, by manually, through a data generation tool, it can be synthetic/fake too. But the fake data wouldn’t be that challenging while testing, and as a result, it may not help to find the defects accurately. Whereas the real data would be at risk, but if used correctly, as in masking the data, it would work effectively.
Challenges with Test Data
Many don’t know or don’t realize that a tester spends around 30-60 percent of his/her time gathering and maintaining data. Additionally, they have to face several other problems as well. Read the below to find out what they are.
- The testing teams usually don’t have access to the data sources.
- Developers delay in giving the production data to the team, and that prolongs the testing or development period.
- Some data depends on other data, and they together make sense. It becomes complicated if you don’t have access to that particular dependent data.
- Loads of data.
- Frustrating and time-consuming data refreshment as the team has no direct access to self-refresh the database – It could even take days and weeks.
Now despite all these difficulties, there is a wonderful solution, and we know you can’t wait to hear it. Its test data management. More to explore, it’s down below you can follow.
Test Data Management Definition
It is the process of managing the bulk test data coordinating with the automated test and fulling their needs—no heavy involvement of humans in the process whatsoever. Meanwhile, it is also responsible for developing the required data for testing, making the life of the tester easy. In other words, it duplicates the original data and, without a doubt, works as efficiently as the original one.
Test Data Management Best Practices
You might be already wondering how to cope up with such a hefty job. But, one thing is for sure it wouldn’t be that hectic if you practice what’s best and legit preach your team the same. We have listed down five best practices for you to follow in test data management.
1. Protect the sensitive data: Ensure the security of the data that you are going to involve in the testing process. Follow the masking strategy of test data management; it secures and provides the team with just the right information.
2. Set up the appropriate replica: Efficiently carry out the duplication of the data for testing; otherwise, the process could end up in sheer failure. Posing critical challenges is necessary to check the performance and quality of the software.
3. Plan and use: Don’t shy away from being picky. Plan your data and use it sensibly. With selective data, you can ensure a much better approach to management. You would need to eliminate it as you can’t use all the data.
4. Regular maintenance of the data: The maintenance of your data is essential, yet it is very costly. Find a cost-effective way to store, manage, access, and update all of your data regularly.
5. Audit the test data: To ensure it represents the workloads in the production.
Test Data Management Challenges and Solutions
In all honesty, some of these reasons are the prime cause why most modern-day businesses still approach the age-old techniques of test data management. Be it an automated test data management tool or proven traditional methods, there are challenges in everything and everywhere. These are some of the real-time challenges businesses face, but the cool thing is we gave the solutions too. Find the list down below.
- Shortage of data for testing, the original data is subjected to confidentiality, and everyone isn’t allowed to view it. There arises a scarcity of data, and there are many other reasons for it. To overcome this, you can use an efficient test data generation tool.
- Data vulnerability is a huge problem; often, organizations get into legal troubles and would potentially lose a lot of money. The best way and the only way to fix this is to mask the data meticulously.
- The secure storage of test data is an actual question. Though there is a pretty straightforward answer, people don’t prefer solely due to its costliness. It’s an excellent investment to make if you are so keen to protect, correct, reuse, audit, and maintain your data. Use a test data management tool; it is a proficient way to tackle the issue.
Benefits of Test Data Management
- It first reduces the data security risks with most qualified masking techniques.
- It provides storage to organizations to store the data.
- It offers automated test data management without much human involvement in the process of doing so.
- It helps to improve the quality of the software very quickly.
- It helps to prevent bugs and other rollbacks in the software.
Who needs test data management?
The organizations that deal with highly sensitive information like health, banking, and more are supposed to use such tools. But if looked practically, every data is essential and subjected to confidentiality in one way or another. Needless to say that all sorts of data should and must be protected.
Well, if you want to improve the quality of the software or application, sometimes you need to take risks or at least invest in reducing the risk. Again eventually, quality matters step ahead and think about each step in the process of testing or developing the software or applications qualitatively.
If you still have a related question in software testing and management, you can check our blogs because we like to give answers to all your questions. Do subscribe and always keep learning.