BOOK A DEMO
START FOR FREE
icon icon
BOOK A DEMO
START FREE TRIAL
On this page
Manage multiple data sets
Test Management 'How to' guides Agile in QA
7 min read
August 27, 2025

How to generate and manage multiple test data sets?

Being able to generate and manage test data sets is crucial for maintaining high standards of quality and performance in software development. As systems grow more complex, creating robust and reliable test data becomes increasingly difficult, taking your time, energy, and resources. Ensuring test environments have accurate and varied data demands all your expertise and attention, otherwise you might end up with delays and inconsistencies. So how do you generate test data sets and manage them while tackling all the potential challenges? This practical guide (with an in-dept video explanation) will equip you with everything you need to handle complex testing scenarios with confidence and precision.

photo
photo
Robert Weingartz
Nurlan Suleymanov

How important is test data management in modern QA practices?

Did you know that 85% of data projects fail
due to poor data management and quality? It shows how important data management is. And it is the same in QA and software testing, where the value of test data is not any less significant.

So why can the role of test data management not be overstated in QA? First, it is essential to understand the impact of efficient test data management on overall software quality and delivery timelines. But it is not only that, there are set of components that make it so crucial. Here’s why managing and generating multiple test data sets is crucial:

1. Enhancing Test Coverage and Accuracy

Proper test data management ensures that all possible scenarios, including edge cases, are covered. This leads to more accurate testing outcomes, helping to identify potential issues early in the development cycle.

2. Reducing Time and Cost

By automating the generation and management of test data sets, teams can significantly reduce the time and resources spent on manual data preparation. This not only speeds up the testing process but also lowers the associated costs.

3. Improving Test Environment Consistency

Consistent and reliable test data is vital for maintaining stable test environments. This consistency ensures that tests are repeatable and reliable, leading to more predictable and trustworthy results.

4. Facilitating Continuous Integration and Continuous Deployment (CI/CD)

Efficient test data management supports CI/CD pipelines by providing up-to-date and relevant data sets for automated testing. This integration helps in delivering high-quality software at a faster pace.

5. Enhancing Collaboration and Reusability

Centralised test data management systems enable better collaboration among team members. Reusable data sets can be easily shared across different teams and projects, promoting a more collaborative and efficient work environment.

6. Ensuring Compliance and Security

In industries with stringent regulatory requirements, managing test data effectively ensures compliance with data protection standards. Proper anonymisation and handling of sensitive data are critical to avoid legal and financial repercussions.

why you should create and manage multiple data sets

Ideally anonymisation should be carried out before it is used or reaches a lower environment. I prefer doing so as a part of database synchronisation or snapshot creation. That is, the infrastructure automatically handles it as a part of the process; whether it be via pipelines, manually triggered (script), etc.

Onomazein Posted in Software Testing Reddit thread, 2 years ago

By understanding and implementing robust test data management practices, you can significantly improve your testing processes. This enhances the software’s overall quality and aligns with business objectives, ensuring timely and cost-effective project deliveries.

But how do you do this? Is there a solution to streamline the process for you?

In the next section, we talk about aqua cloud, a solution tailored not only for test data management but the whole test management process. There will be a video waiting for you at the end of the section, so the explanation will be crystal clear.

How to manage multiple test data sets effectively with aqua cloud?

aqua cloud is an AI-powered test management solution designed to streamline and enhance your testing processes. With features like AI-driven test case and requirements management, seamless integration with automation tools and bug-recording gem Capture, and efficient management of software tests, aqua cloud is revolutionising the way QA teams operate. But how does it help with test data generation and management? Stay tuned: we will show you in the step-by-step guide.

Step-by-Step Guide to Generating and Managing Multiple Data Sets with aqua cloudĀ 

Effectively managing test data is a must for successful QA processes. aqua cloud offers advanced capabilities to streamline this task, using AI and seamless integration features. Below are detailed steps on how aqua cloud can assist you to generate multiple data sets and manage them efficiently:

1. Prepare and Input (or Import) Your Test Data

Importance: Proper preparation and input of test data lay the foundation for accurate and comprehensive testing. Ensuring that your data sets are aligned with your test cases and requirements is crucial for effective test execution.

Step: Begin by preparing the data sets based on your test cases and requirements. Determine how many data sets you need and specify the necessary variables. You can input this data into the system by importing it, creating it manually, or generating it with AI.

With aqua cloud’s assistance:

  • You can generate test data with a single click directly from your test case or requirement, simplifying the initial data preparation process.
  • Use the data-secure AI Copilot to help create your test data sets.

2. Add and Use Placeholders in Your Test Cases

Importance: Using placeholders allows for dynamic data insertion during test runs, ensuring that your test cases adapt to the most relevant and up-to-date data, which enhances the accuracy of your test results.

Step: To dynamically use your test data during test runs and execution, employ placeholders in your test steps. These placeholders will automatically use and replace the data from your data sets.Ā 

Empowered by aqua cloud:

  • Implement placeholders effortlessly within your test cases, allowing for flexible and efficient test execution.

3. Reuse Test Data Across Test Cases

Importance: Reusing test data across multiple test cases ensures consistency and reduces redundancy, saving time and resources by avoiding the need to recreate data sets for each test case.

Step: Rather than copying and duplicating data sets, connect your existing test data from one test case to another. This practice enhances efficiency and consistency across your test cases.

Streamline with aqua cloud:

  • Link existing test data to new test cases seamlessly, as covered in our ā€˜Reusabilityā€™ video. This feature promotes data reusability and saves time by reducing redundant data creation efforts.

4. Track Dependencies Between Test Data and Test Cases

Importance: Understanding the dependencies between test data and test cases helps you manage changes effectively, ensuring that all related test cases are updated accurately when test data is modified.

Step: It’s crucial to understand which test cases will be affected when you edit your test data. Keeping track of these dependencies ensures that all related test cases are updated accurately.

Simplified by aqua cloud:

  • Trace dependencies with a single click using aquaā€™s dependencies diagram. This visualisation helps you maintain accurate and up-to-date test cases by showing the relationships between your test data and test cases.

5. Add Test Cases for Every Value Set in Your Test Data Set

Importance: Ensuring comprehensive test coverage requires adding test cases for every value set in your test data, including positive, negative, and edge cases. This guarantees that all potential scenarios are tested thoroughly.

Step: Ensure that every value set in your test data is covered, including positive, negative, and edge cases. Comprehensive coverage of all possible scenarios is vital for robust testing.

Enhanced by aqua cloud:

  • Add test cases to your test scenarios for each data set with just one click. This functionality guarantees that all potential scenarios are tested, enhancing the thoroughness of your QA process.

And here is the practical video explanation of these steps, covered fully by our customer success manager, Robert Weingartz:

Love what you see? So why wait? aqua is the ultimate solution for your whole test data set generation and management. Powered with German quality, this test data management system provides you with a chance to effortlessly generate test data sets and manage them, thanks to our innovative AI capabilities. But its AI capabilities do not end there: you can generate test cases from requirements in just a few seconds, saving you a lot of time and resources. aquaā€™s AI Copilot is your testing ally, helping you in every step of the process. Full traceability, 100% visibility, advanced 1-click bug-tracking integration with Capture, and much more. Try aqua cloud and test how a single test management solution can take away the pain of testing from you.

Generate and manage multiple data sets with just a few clicks

Try aqua cloud for free

Conclusion

The process of generating and managing multiple test data sets is a critical aspect of effective test management. So you either choose the right solution along the way, or you get lost in the maze of these multiple data sets. With aqua cloud’s innovative AI-powered capabilities, this process is streamlined and efficient. By preparing, inputting, and organising test data sets based on requirements or voice prompts, aqua cloud simplifies the often complex task of data management in QA workflows. So why wait? Contact us and see your testing efforts elevate to the highest levels with just a few clicks.

On this page:
See more
Speed up your releases x2 with aqua
Start for free
step

Related topics

Test Management 'How to' guides Agile in QA Best practices

FOUND THIS HELPFUL? Share it with your QA community

FAQ

Why is using multiple data sets important?

Using multiple data sets is crucial because it creates a path for comprehensive testing. By testing with different data, you can:

  1. Identify edge cases ā€“ Catch bugs that only appear with specific data inputs.
  2. Improve accuracy ā€“ Ensure the system works for a variety of real-world scenarios.
  3. Enhance reliability ā€“ Make sure your application handles diverse user data correctly.

In short, you keep your application robust, functional, and reliable across various situations.

How to generate a dataset?

  1. Use Existing Data ā€“ Gather data from public sources or company databases.
  2. Leverage Automated Tools ā€“ Use tools like aqua cloud, Mockaroo or Faker to generate synthetic data.
  3. Manual Collection ā€“ Collect data manually through surveys, forms, or web scraping.
  4. Simulate Data ā€“ If testing, simulate data based on specific test cases or business rules.

Why create multiple databases?

Creating multiple databases helps keep data organised and secure. For example, you can separate data for different departments or projects, which makes managing it easier and safer. This also boosts performance, especially when you have a lot of data since no single database gets overloaded. When it comes to backups or recovery, itā€™s simpler to work with smaller, isolated databases rather than dealing with one massive one. So, itā€™s all about efficiency and minimising risk.

Related Articles
Best practices
16 min read
Mastering SAP Project Management: Tools, Tips & Comparisons
By
Multiple Authors
Best practices Test Management
17 min read
15 Essential Project Management Principles for Success
By
Multiple Authors
'How to' guides Best practices Test Management
9 min read
Best Project Management Templates for Software Testing in 2026
By
Multiple Authors

Related topics

Test Management 'How to' guides Agile in QA Best practices
Home » 'How to' guides » How to generate and manage multiple test data sets?