10 Best Test Data Management Tools to use in 2022 & beyond
One of the most critical components of software development is test data! Without test data, it’s just not possible to deliver any software that meets customer’s expectations. Test data ensures software’s security, integrity, and compliance. Since it plays a crucial role, it’s important to have an appropriate framework to handle it. That’s why we have crafted this post for you, listing the best test data management tools.
Before we get to the tools, let’s try to understand the basics of test data management.
Table Of Contents
- 1 What is Test Data Management?
- 2 Choosing a Test Data Management Tool: Comparison Criteria
- 3 Top 9 Test Data Management Tools
- 4 Key Features of ideal Test Data Management Software
- 5 Properties of Good Test Data
- 6 Why is the Role of Test Data Management Important?
- 7 Automating With Test Data Management
- 8 What Are The Different Types of Test Data?
- 9 Summary
- 10 Frequently Asked Questions
What is Test Data Management?
Test Data Management (TDM) primarily aims at creating, managing, and maintaining the test data to perform efficient testing. This process enables the QA teams to follow a streamlined approach to control a project’s data, files, and policies.
It is through test data management that QA engineers can segregate the test data from the production data, track bugs and perform other QA processes. A primary benefit of leveraging test data management is its ability to minimize the test data size as well as centralize the testing documentation.
Generally, a test data process has the following five stages:
- Planning: At this primary stage, the QA engineers plan the types of tests to be executed, analyze what may be required to perform these tests, and create comprehensive documentation.
- Analysis: QA engineers collect the data and consolidate critical information at this stage. These include info regarding data access, backups, and storage.
- Design: The design stage takes place before the test data management implementation. At this stage, the strategy for data preparation is designed. Here, QA engineers can choose from synthetic data or clone the available databases to perform testing. Testers should be able to identify the sources of data, its providers, as well as the environment in which the data will be loaded.
- Build: At this stage, the QA engineers finally implement the plans and strategies discussed in the design and analysis phase.
- Maintenance: To achieve successful test data management, QA engineers troubleshoot and fix the errors necessary to perform effective QA while responding to the test data request and making updates on the go.
Choosing a Test Data Management Tool: Comparison Criteria
Today, a plethora of test data management tools are available for QA engineers to leverage. Every tool comes with its specialties and drawbacks.
To ease the process of selecting the best possible tool for test data management, the following comparison criteria may be taken into consideration:
- Should have an engaging User Interface (UI): A user-friendly UI is a common trait for any tool. This is important for a test data management tool as it becomes easier to create and manage test data.
- Ease of usage: The test data management tool should be easy to use. Everyone, including the developers and the managers, should be able to use this tool without special training.
- Ease of integration: The test data management tool has to work with many third-party extensions. Hence, the tool of choice must seamlessly integrate with standard CI/CD tools such as JIRA, Azure, etc.
Top 9 Test Data Management Tools
It is a leading cloud-based test automation tool that uses natural language and an easy-to-understand interface, allowing users to automate applications of any type. Testsigma enables users to plan, develop, execute, analyze, and make reports for continuous testing in DevOps and Agile. Testers can build end-to-end tests five times faster with English scripts for mobile apps, APIs, and web apps. The scripts can self-heal, allowing maintenance-free testing.
Testsigma also has a marketplace that provides add-ons for data generators and automated actions. Users can access it instantly and can customize it based on their preferences. The platform offers features to build custom add-ons for any data generator, workflow, and action using APIs and SDKs. It facilitates a shift-left approach by involving everyone, including project managers, developers, and QA Teams, to collaborate on applications and projects without any prior knowledge of technical skills. With AI-powered maintenance, preset building blocks, and simple integrations, Testsigma delivers reliability to test automation.
K2View is a data product platform that democratizes data access in an organization. It continuously syncs, transforms, and gives access to data via data products. The tool delivers a real-time and holistic view of business enterprise (device, customer, order, claim, etc.) to any data consumer. Every day, almost 5+ billion data queries are executed on this platform, delivering 200ms of response time for each data consumer query. K2View Data Product Platform also manages multiple workloads (like data pipelining, data tokenization, customer 360, and cloud migration) at a fraction of cost and time and at a massive scale.
Users can deploy multiple architectures, such as
- Centralized data fabric
- Multi-domain data hub
- Federated data mesh
It can also be deployed in the cloud as an integration platform as a service (iPaaS), on-premises, or on a hybrid platform. Testers can integrate and organize data from different data sources into micro-databases and deliver them in real time to the target system using any delivery method (messaging, CDC, API, virtualization, ETL, and streaming).
It is a programmable data infrastructure that automates the data in digital transformation programs. Delphix, with its multi-cloud data platform, allows enterprises to modernize outdated apps 20% faster, release software 50% more quickly, and facilitate cloud migration 30% faster. It does all these tasks while maintaining compliance with CCPA, HIPAA, GDPR, and other data privacy regulations.
Delphix can make a complete clone of databases like MS SQL, PostgreSQL, Oracle, DB2, MySql, and Oracle EBS, SAP, in minutes without any storage cost. Its capabilities include:
- Virtualization: Allows users to use up to 10 times of storage allotted to Delphix.
- Masking: Offers profiling and discovery options for sensitive data, which should be masked before forwarding for testing, UAT, and other environments.
- Replication: Allows users to replicate any data from the production network to the test network.
- Time Travel: Syncs with production databases, allowing users to create database clones anytime.
- Automation: Users can call Delphix operations via REST API because the Delphix DataOps Platform is an API-first product.
4. AVO Test Data Management
This test data management tool helps users generate relevant and reliable production-like test data quickly. The data generated with AVO iTDM allows testing experts to speed up their entire testing process. It automatically identifies and manages PII (data discovery), offers data provisioning and generation, and secures sensitive data for PII compliance. AVO iTDM supports open architecture and custom modules. It is built and deployed using open-source technologies and container frameworks and can handle billions of records simultaneously. With the AVO Test Data Management tool, users can:
- Fasten application delivery by expediting testing
- Identify and resolve non-compliant data issues in non-production environments
- Generate and deliver relevant data downstream
- Comply with configurable and continuously evolving on-demand data privacy regulations
It is a SaaS-based end-to-end test case management tool that facilitates the entire QA process. PractiTest:
- Supports documentation
- Provides a roadmap from requirements to test cases
- Has the ability to create/run/edit test cases
- Integrates the log defects into the defect management system
- Provides better control and visibility for all the interactions via easy-to-understand reports and dashboards
Whenever you create a test case in PractiTest, any changes made afterward from any platform location will be reflected automatically throughout the application. It saves a considerable amount of effort and time during the QA process.
This platform allows testers to:
- Run tests locally and in the cloud
- Integrate with CI/CD systems
- Capture logs and screenshots of test runs
- Prepare detailed reporting of each test run with graphs, stats, and other information
Testim can easily align with a shift-left paradigm where QA experts and developers can write their test cases right from the beginning without overwriting each other’s changes. This gives them the flexibility to collaborate and write automated test cases via built-in functionalities.
7. Tricentis qTest
It is an enterprise test data management tool with the facility to integrate with DevOps and third-party tools. As a test management tool, qTest enables the following:
- Run tests with centralized control and orchestration of workflows
- Ability to share and reuse test cases for ease of creating and maintaining test cases.
- Integration with open-source and third-party tools such as Jira, GitHub, Selenium, etc.
- Provides customized and shareable test data reports from 60+ report templates.
8. QA touch
QA Touch test management tool offers a natural and intuitive method of execution and comes with an in-built allocation and tracking feature. Users can copy and move the test cases within modules in a project as well as across projects. QA Touch allows the creation of test cases, test suite bundling, third-party integrations, and test reporting.
Other key features include:
- Requirement mapping with appropriate test cases.
- Mind Map feature to scribble and visualize future testing strategies.
- Creating and managing BDD test cases.
- Custom project reports, test coverages, and real-time status of release cycles.
- Integration with tools such as Jira Server, Bugzilla, and Lighthouse.
The TechArcis Test Data Management automation allows testers to reduce build errors. Additionally, the tool provides service virtualization, which eases test data creation and management.
Key features of TechArcis include:
- Test data and test environment automation
- Provides accurate data for effective test results
- Enhanced test coverage with better-quality test data
- Reduced data exposure for risk mitigation
- Data masking to enable the privacy of data
- Regulatory compliances such as HIPAA, SOX, PCI, etc.
10. MOSTLY AI
This synthetic data platform allows you to generate synthetic data for different testing use cases. Synthesization is a great way to anonymize sensitive customer data and you can also use the process to subset or upsample datasets into smaller or bigger, realistic versions of themselves. Synthetic data can be used in the following ways:
i. to replace production data
ii. to subset large datasets into smaller, more manageable ones
iii. to create bigger datasets from small ones for performance and stress tests
iv. to generate erroneous and diverse data for reliability testing
Key Features of ideal Test Data Management Software
- Easy-To-Use User Interface: Professional QA engineers are aware of the importance of attractive and user-friendly app UI. A test data management tool with an attractive UI makes it easier for team members, including Dev, QA, and all other stakeholders, to overview the project quickly. Teams spend their time on something other than specialized training.
- Enable multiple and customized access: A good application is made when individuals come together from diverse backgrounds, such as project managers, developers, stakeholders, testers, and so on. Some of these individuals would require read-only access, whereas others would need master access, depending on their roles and responsibilities. The test data management tool should provide the facility of multiple as well as customized access so that permissions can be granted accordingly.
- Tracking and traceability: When working in an agile environment, it helps to trace every change made to the application. The test data management tool should be able to provide the required tracking and traceability. This enables the teams involved in the project to follow the changes made by other departments and provide the necessary accountability for every individual.
- Facilitate scheduling and organization: Effective planning and scheduling are critical to every successful project. The test data management tool should be able to assist with scheduling, planning, resource management, and organization. A good test plan is necessary to ensure everything is in its place, which becomes even more critical in the case of complex and large projects. A reliable test data management tool should provide essential insights into how the dev and QA teams will execute the scheduled test plans and deliver the project on time and as per the desired quality.
- Provide Metrics and monitoring: The test management tool should be able to provide real-time metrics and monitoring to ensure the project is being executed as per the defined timeline and budget. High-quality test data management tools feature customized configuration options to enable tracking on demand as well as determine the project goals to ensure timely releases. The tool can compare the progress of the project in real-time with the predefined timelines, hence reporting issues and delays to the stakeholders.
- Flexibility: Every test plan and project has its unique requirements and goals. A practical test data management tool is able to adapt as per the project expectations and provide customized features to the teams. This means testers can add or eliminate the fields in a report or even optimize the access to the stakeholders as and when required.
Properties of Good Test Data
A test data should have the following properties:
- The test data should clearly declare the entity or scenario it is going to validate.
- It should be able to complete the number of scenarios/cases to be tested.
- It should be segregated based on quality to ensure more defects are found.
- It should be easier to group specific scenarios or cases for better clarity and coverage.
- There should be a good balance between positive and negative test cases.
- Test cases should be ranked based on priority, so tests may be prioritized when teams run short on time.
- Test cases should be automated effectively so that in case of test failure, no other tests stop the overall execution.
Why is the Role of Test Data Management Important?
- Enhances effectiveness: When the test data management tools are in place, the overall effectiveness of the testing, as well as app delivery, enhances significantly. By enabling high-quality test data, testers can increase comprehensive test coverage, accelerate high-quality app delivery, and improve process agility.
- Saves time and cost: Test data management tools enable quick provisioning of the necessary test data. This allows testers to find bugs early and eventually save the cost of fixing them at later stages. Testers also save time generating QA reports for the stakeholders, giving them more bandwidth for innovation.
- Ensures quality and privacy: Test data management tools are secure and half high quality. This allows the associated teams to adhere to the compliances and regulations of the organization. Prevention from a data breach also results in maintaining client trust as well as keeping the organization ahead of the competition.
Automating With Test Data Management
Implementing an effective test data management strategy is critical for successfully creating and maintaining test automation scripts. Here are a few tried and tested methods that can be leveraged for effective QA implementation.
- Externalize the data: Always externalize the automation data to files like .csv. Since the data may change with time, it is essential that this change does not affect the source code and that testers can update this data without struggling with the code.
- Have unique prerequisite data for each automation cycle: Creating prerequisite data within automation whenever possible ensures the data is unique for every automation cycle and testers do not face issues with reusing the same test data.
- Leverage all test environments: Testers should remember that most projects run on multiple test environments. When creating the automation strategy, it is essential to undertake this fact so that test data management becomes scalable and flexible.
What Are The Different Types of Test Data?
The following are the common types of test data:
- Blank data: This data measures how the application responds in case no data is entered into the system.
- Valid test: This test identifies how the system reacts in case correct data is entered. A valid test is used to validate the primary feature of the app.
- Invalid test: This test measures how the app performs in case invalid data is entered into the system.
- Boundary conditions: This type of test validates multiple combinations of data.
- Huge test: This test analyzes if the app is prepared for additional tests such as load testing and performance testing.
Every test data management tool available in the market today has its own capabilities and weaknesses. When investing in a particular test data management tool, it is recommended to begin with an evaluation criterion in which the business needs are defined against what the test data management tools offer.
This not only helps with researching the best possible tool in the market, but also enables us to choose from the wide range of tools that provide similar functionalities.
Frequently Asked Questions
Is Excel a test management tool?
Yes, in some cases, Excel provides simple and short-term test management solutions. However, as the tests and the project get complex, Excel fails to expand on the tasks to be performed by testers who need more than basic spreadsheets for managing test cases.
Is Jira a test management tool?
Ideally, Jira is a repository that facilitates documentation and tracing of issue reports. However, JIRA does not provide any test plans. When tests are executed in JIRA, testers cannot perform automation testing from within the tool. This becomes a bottleneck, especially when working in a CI/CD environment.
How does test management work?
The Test Management process can be divided into two main parts:
- Risk Analysis
- Test Estimation
- Test Planning
- Test Monitoring and Control
- Issue Management
- Test Report and Evaluation
What are Major Test Data Management Challenges?
The following are the common challenges testers face with managing test data:
- High cost associated with complete production cloning instead of performing data sub-setting.
- There are possibilities of poor test data outcomes if the team relies on invalid or outdated data.
- Since the same test data is available across teams, test data corruption is possible.
- Data is prone to leakage and breach, and safety standards and compliance should be adhered to.
- There may be costs of storage and infrastructure associated with the generation and provisioning of test data.