May 10, 2022
Meaningful test data is a critical aspect of any successful QA process. It would be best if you refrained from using production data directly. Having a systematic approach for building test data is also very important, as otherwise, there is a chance of missing important test cases.
Hence in this article, we will talk about how to generate, manage, and use test data to achieve the best results. We will discuss the different techniques to generate efficient test data. You’ll learn how to manage large amounts of test data generated in each regression cycle. Then we will also briefly cover tools that will help you with data management.
Let’s start with how we can generate test data.
How to generate Test Data
There are three common ways:
- Manual Test Data Generation
- Automated Test Data Generation
- Backend injection.
Manual Test Data Generation
Manual test data generation is a process of generating test data on your own, with the help of your QA team members, or by developers. The manual method requires you to prepare a list of items used for testing and then create sample data for them.
It is the direct and most straightforward way to generate test data. The manual test data is often generated at the beginning of project implementation and is created in a manner that includes all possible combinations of inputs and outputs. This method is the most time-consuming and is typically used to cover project-specific edge test cases and input/output combinations that can’t be generated automatically.
Automated Test Data Generation
Automated test data generation is done with the help of software tools that automate the whole process from start to finish. The main benefits of this method are vast generation speed, as well as the accuracy of generated data. It is an effective way to reduce the time taken to develop, maintain, and execute tests compared to using manual test data, which is prone to human error.
Different automated test data generation tools support various intelligent features out of the box.
The key features of automated test data generation
- Realistic / Real-world Test Data
- System integration is supported
- Data Synthesization
- Data Anonymization
Backend injection is a process of injecting test data into the backend for testing. Here’s how this usually looks: a tester will write a relevant SQL query, and then inject it into the database. It is also a great method to quickly generate a large amount of test data. However, compared to automated test data generation – backend data injection requires less technical expertise.
Backend injection can be used in different scenarios such as:
- To test and debug your application without user interaction
- To create a large amount of data for testing purposes
- To avoid the expensive cost of manual data generation
Typically, we suggest using backend data injection when software design has not been finalized yet or when UI is unavailable.
There are several third-party tools available that we can use to generate test data. These tools can be used to automate the generation of test data for specific types of test cases or for a new software application. Most third-party tools can pump data (which is similar to real-time data) in huge volumes for the ideal testing conditions. Third-party tools can generate accurate and domain-specific test data and populate real-time data in the system. The downside is it is typically a costlier solution compared to other techniques we’ve discussed.
Managing the test data to achieve the best test results
Generating the sample test data is just the first step. The real challenge is managing the test data gathered from running each test case in each regression cycle from regression to release.
Efficient test data management results in effective software testing, but it’s not easy. In a recent report, only about 45% of testing teams have reported managing test data and test environments to be challenging.
The main reason behind this is that test cases fail for many reasons in a regression run. Different reasons can include bugs, incorrect testbed data, changed product behavior, infrastructure issues, etc. We need a system in place to effectively analyze and address the failures.
Hence test data management is an essential aspect of the testing process. It helps us manage test data and improve the efficiency of testing processes by analyzing it and identifying issues with the application’s performance.
Managing test data is difficult as it often gets generated in a large volume. It is also time-consuming because of the amount of manual work involved. This is where the Test Case Management System (TCMS) or Test Data Management Software (TDMS) comes in.
Uses of Test Data Management Software
- With the help of TDMS, we can automate all the tedious tasks involved in managing your test data and spend more time on what matters – testing!
- TDMS helps to keep track of the entire test data. Usually, test results from each regression cycle are stored here.
- Over time, we will end up with massive test data in TDMS, which helps us manage, analyze, and visualize the data to identify problems and improve testing processes.
How to select the ideal Test Data Management Software for your testing project
The best TCMS lets you collect and organize test data to enable you to test new features and gather feedback quickly.
There are several TDMS systems available in the market. Each product is unique and offers different features. While selecting the ideal TDMS, we can keep the following key points in mind:
There are several test data management tools available in the market. The ideal tools excel mainly in the following four areas. Let’s quickly understand the summary of the evaluation criteria we can use while comparing these products:
- User Interface (UI): An exemplary user interface lets users easily consume features, even complex ones. UI is vital as it helps create data sets and view reports.
- Usability: Good usability means the software is responsive and performs well without bugs. Anyone on your team or workplace should be able to use the software without any issue.
- Integrations: Most test management software integrates with Azure CI/CD tools and Jira.
- Value for Money: Obviously, every business has unique requirements and budget. You can choose the TDMS which best fits your budget.
Test Data Management Software Key Features
Most of the test data management solutions available in the market have several features in common. The following are the key features you should be looking for while choosing test data management software.
- Data masking: Data masking removes sensitive information and Personally Identifiable Information (PII) such as mobile number or credit card details, house number, and payment info from production data. Test data can share post-data masking data with testing teams. This ensures you stay compliant with data privacy regulations such as GDPR.
- Targeted testing: Testing the complete software each time the software is updated is resource-heavy. It takes more time and consumes a lot of resources. Targeted testing lets us test only those sections of code modified. This speeds up testing and consumes fewer resources.
- Intelligently sized datasets: The best test data management software can create large enough datasets to generate optimum results but not so large that it becomes resource-heavy.
The best test data management tools in 2022 include:
- Solix Enterprise Data Management Suite
- CA Test Data Manager (Datamaker)
- Microfocus Data Express
- IBM Test Data Management
Apart from the above most companies tend to use their own in-house Test Case Management Systems to handle test data effectively. The most effective Test Data Management Software comes with all the key features mentioned above at the best price.
Now that you’ve learned more about test data usage, you’re one step closer to achieving a robust end-to-end test coverage with testRigor’s no-code automation testing.