Optimizing Software Testing with Effective Test Data Management Tools

Heather Brooks

When it comes to testing, having a working test case is not enough. To test real-world scenarios, you need to mimic user behavior. Since data is the currency of the online world, a good test case will include real-world data for testing. But here’s the main question: how do you obtain this data? Do you leverage the production database for this? Absolutely not! Even the slightest change to production data could result in serious violations, which are definitely not good for your business. We need ways to generate data that is as close to real-world data as possible, is secure, is compliant with security and legal requirements, and can be readily accessed and reused. All this should be achievable without having to put in a manual effort. This is where test data management (TDM) comes into the picture.

What is test data management (TDM)?

Test data management aims at giving a holistic solution to creating, managing, and maintaining the data. This includes identifying and selecting appropriate data sets, creating synthetic data, and ensuring the data is accurate, consistent, and representative of real-world scenarios. With good TDM software in place, you can be rest assured, knowing that you need to focus on creating good test cases rather than generating vast amounts of data.

What should good data look like?

Good test data should possess certain properties to ensure that it is effective in testing the software. Some of the key properties of good test data include the following:

Relevance: Test data should be relevant to the system being tested.
Validity: Test data should be valid, which means that it should reflect real-world scenarios and data types that the system is likely to encounter.
Completeness: Test data should be comprehensive enough to cover all possible paths and outcomes in the system being tested.
Consistency: Test data should be uniform and follow a standard format, structure, and naming convention.
Accuracy: Test data should be free of errors, typos, or inconsistencies.
Security: Having secure test data is essential, meaning it should not contain any sensitive or personally identifiable information that could be used for malicious purposes.
Scalability: Test data should be scalable, which means it should handle large volumes of data and support performance testing.
Maintainability: Test data should be easy to update, modify, and manage over time.

What are TDM tools for?

Test data management (TDM) tools are software tools designed to support and automate the test data management process. These tools provide a range of features and functionality, including:

Test data generation: TDM tools can create realistic test data sets based on specific requirements and scenarios.
Data masking and obfuscation: TDM tools can modify sensitive data in a way that preserves its structure and integrity, but hides or disguises the actual values to protect privacy and security.
Creating data subsets: TDM tools can create smaller, representative subsets of production data for testing purposes to reduce data volume and improve test efficiency.
Data profiling: TDM tools can analyze the characteristics of data sets, such as the frequency of values, data type, and consistency, to identify potential issues and defects in the data.
Data versioning and management: TDM tools can manage different versions and configurations of test data, as well as track changes and updates to ensure data accuracy and consistency.
Integration with test automation frameworks: TDM tools can integrate with the test automation frameworks to provide test data inputs to automated test scripts.

Benefits of using TDM

We have just discussed what TDM is and what these tools have to offer. However, let’s also look at the benefits of applying TDM to organizations. Here are the main ones:

Improve Test Coverage: TDM can help create comprehensive test data sets that cover all possible scenarios and inputs, improving test coverage and identifying more defects and issues.
Time and Cost Savings: TDM can help reduce the time and effort required for testing by providing automated support for creating, managing, and manipulating test data.
Improved Test Quality: You can improve the quality of your testing by using test data that is as close to the real world as possible. This will, in fact, help catch issues that might occur when the end user interacts with the application.
Compliance and Security: TDM can also help provide compliance with regulations and security standards by protecting sensitive data and ensuring it is properly managed and secured.

Leading TDM tools to consider

Let’s take a look at some of the popular choices for test data management tools.

CA Test Data Manager

CA Test Data Manager is a comprehensive test data management solution that enables teams to create, find, and reserve test data to streamline testing processes. The tool provides synthetic data generation capabilities, allowing you to create realistic test data sets without relying on production data. It also offers data masking features to protect sensitive information, ensuring compliance with data privacy regulations. CA Test Data Manager supports data subsetting, helping to create smaller and more focused data sets for efficient testing. Its automation capabilities enable continuous testing and integration with popular CI/CD tools, reducing the time and effort required for testing.

Datprof

Datprof offers a suite of TDM solutions designed to simplify the process of creating, anonymizing, and analyzing test data. Datprof Subset enables you to create smaller, more focused test data sets by selecting specific portions of your production data. This helps to improve test efficiency and reduce storage and processing requirements. Datprof Privacy provides data masking and anonymization capabilities, ensuring that sensitive information is protected while maintaining data integrity and compliance with privacy regulations. Datprof Analyze allows you to examine the structure and content of your test data, identifying potential issues and inconsistencies that could impact testing results.

DataVeil

DataVeil is a test data management tool specializing in data masking solutions. It ensures that sensitive information in your test data is protected and compliant with privacy regulations while maintaining data integrity. DataVeil supports a wide range of data sources and platforms, including SQL Server, Oracle, MySQL, and PostgreSQL. The tool provides a variety of masking techniques, including randomization, substitution, and redaction, which can be tailored to specific requirements. DataVeil’s dynamic data masking capabilities enable real-time data protection without affecting database performance, making it an ideal solution for managing sensitive test data.

AVO Intelligent Test Data Management

AVO’s iTDM can give you production-like data with just a few clicks. Some of the capabilities offered by this tool include AI/ML-based synthetic data generation, support for open architecture with easily pluggable custom modules, data security even at the lowest level of data, and discovery of non-compliant data in non-production environments. The pricing for AVO iTDM is generally not publicly available, and interested organizations will need to contact AVO to request a quote.

Delphix Test Data Management

Delphix provides a TDM platform that helps teams populate test environments with realistic and compliant test data. The tool offers powerful masking capabilities, virtual test data provisioning, and version control for data sets. Delphix also integrates with several tools and data sources. Its interfaces are considered user-friendly and easy to use. Since Delphix is an API-first product, you can call its operations using REST API. Delphix offers different pricing models and plans depending on the specific needs and requirements of the organization.

How to choose the right tool?

When it comes to picking a tool, you should always consider your requirements first. These requirements could include the project size, the type of data required, the quantity of data, expected integrations with other frameworks, any industry or security compliances to be considered, teams or users requiring access, scalability scope, and budget allotted for this. Once these points are considered, you can use this reference to decide which tools satisfy your requirements.

Below are some additional points to keep in mind when it comes to picking the right TDM tool.

Good UI: In order to use any tool, it should have a user-friendly interface. Depending on your user base, you can decide if you need a very graphical UI or a more technical look and feel would work.
Easy to use: Irrespective of what kind of UI you choose, whether very simple or something more advanced, it should be intuitive and easy to use for the target users.
Easy integration: Since TDM tools will not be the only part of the process, they need to integrate with other test automation tools, databases, and CI/CD tools.
Pricing model: Consider the budget allotted for a tool. Though open-source tools seem ideal initially, they may lack the security and features of enterprise versions. Since this is a good investment, you might as well consider purchasing a tool.
Good technical support: Though a need for technical support for a TDM tool may not be too obvious, it is always good to have it. Most popular tools also have communities that offer such support and can be used in case of roadblocks.

How to use TDM tools in test automation?

We have seen what TDM is and what it entails. Using the TDM tools mentioned above or any other tool of your choice, you can create a holistic testing process in the following ways.

Identify data requirements: Understand the data requirements of the application under test and identify the types of test data needed for testing.
Create test data: Use automated tools such as data generators or mock data tools to generate test data. This can help to speed up the process of creating test data and ensure consistency and accuracy of the test data.
Manage test data: Use TDM tools to manage the test data, such as by creating data subsets, masking sensitive data, or using data virtualization techniques to provide test data as needed.
Integrate TDM with test automation: Integrate TDM tools with test automation tools to automatically retrieve and manipulate test data during test execution.
Execute automated tests: Run the tests using the TDM-enabled test automation tool to execute test cases with the appropriate test data.
Monitor and maintain test data: Continuously monitor and maintain the test data to ensure that it remains relevant and up-to-date throughout the testing process.

Effectively using test data in automated testing

If you’re not yet familiar with testRigor, it is one of the easiest and most innovative ways on the market to build end-to-end functional automated tests without code, and spend very little time on maintenance.

testRigor makes it easy to create or import large data sets in the Test Data section. Additionally, it is extremely easy to work with test data, including navigating through tables. We invite you to watch this video and take a look at the documentation to better understand how testRigor works.

Final thoughts

Good test data should be well-designed, comprehensive, accurate, and relevant to the system being tested, to ensure that it can effectively validate the functionality, performance, and quality of the software. The tools mentioned above are some of the popular choices for TDM. However, there are other tools as well in the market that might fit your criteria. Most TDM tools are not coupled with testing frameworks. Hence picking a good testing tool will help improve the quality, efficiency, and effectiveness of the software testing process, leading to a better software product and a more satisfied user base.