What Is Test Data Management: A Fool-Proof Guide on Getting a Solid Understanding of the Software
In high-quality software development, rigorous testing is critical for preparing products before release, streamlining internal use, and providing an excellent service for clients.
What is test data management? This crucial step removes crippling bugs and the potential for customer dissatisfaction. To succeed, developers require a supply of test data to properly fulfill the process and a deep understanding of the testing process itself.
This article will cover the process known as test data management to offer enterprise leaders a fool-proof guide to understanding their software.
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What is test data management?
Test data management refers to the process that creates, manages, and delivers a supply of high-quality test data to application teams for review processes.
These non-production data sets reliably mimic an organization’s typical data stream so that systems, applications, and developers can perform rigorous pre-release system reviews.
Test data management is yet another example of the constantly evolving nature of software development vs. manufacturing, where progression within products is defined by their consistent improvement rather than the quality of task repetition. As a result, test data management is not just a box-checking exercise but a simplification and streamlining of the products days, months, and years down the line.
In short, test data management progresses as follows:
- Data creation: Developing the data through production cloning or synthetic data generation strategies.
- Data obfuscation: It’s crucial to identify and obfuscate sensitive data from this process to stop leaks. Strategies such as data masking and data anonymization may help avoid this.
- Data subsetting: Also known as data slicing, this process obtains only a portion of the data during production cloning. As testing rarely requires all available data sets,
subsetting is valuable for reducing storage and infrastructure costs.
- Reviewing: Once data is prepared for use, it’s time to deliver it to the test environment. The test data management process must ensure testing data is provided at the right time and in a suitable format.
- Integrations: It’s equally essential that test data delivery can integrate with existing tools used by the company/client.
- Versioning: Versioning test data repositories allow for perfect repeatability of tests and more granular control of the changes made to the data throughout the process.
Test data management marks another way entities within the SaaS industry are looking to strike a competitive edge against lackluster products. Much like investing in a SaaS SEO strategy or reworking subscription options, this kind of testing can make a product better served to its target audience and automate essential enterprise operations.
Why is test data management critical in software development?
Dedicated test data management can benefit both an organization and its customers.
Primarily, test data management has become so essential because it:
- Provides an overhead view and greater traceability of the test data coverage and defect patterns within the software.
- Significantly reduces costs by spotting potentially software-breaking bugs.
- Provisions data based on testing type. In this process, data is managed in one place, with appropriate data drawn from the same repository. This allows data to be provisioned for different testing types, influencing functional performance and reducing redundant data copies.
- Improves data compliance and security. With data masking an integral part of the data management process, data security and compliance in line with your region’s restrictions are a top priority.
- Offers data reusability. One of the most valuable features of the process and another that reduces costs. Reusable data is sorted and archived in the central repository for future usage, which testers can use in later projects.
- Improves customer trust. A vital advantage of this process is the quality of data and data coverage. Bugs are unraveled long before launching, with these qualities present during the testing process. The result? In a high-quality application with minimum production defects, those of which remaining can be ironed out. In turn, the customer gets an excellent product and recognizes the importance of the test data management process.
The software world is ever-changing, with increasing numbers of companies relying on it to complete simple everyday tasks and business-defining services. As a result, everything from a virtual office phone system to robust cloud storage options needs to be thoroughly reviewed before deployment or risk the reputation, productivity, and security of clients.
Properties of good test data
Significant test data has several properties besides quality, such as:
- Availability: Quality data is meaningless if your tests don’t provide the answers you need, so availability is just as important.
- Realism: Another crucial property that allows for more rigorous testing. Ensure that test data mimics actual production as closely as possible. Otherwise, the processes won’t verify real-world user experiences and scenarios.
- Protection: One of the most common solutions for obtaining test data is production cloning, which can create the risk of exposing personal information through old data. Good data management accounts for this and prevents potential reputation and financial damaging data leaks by opting for alternatives.
How to implement successful test data management
Implementing test data management successfully is easier said than done, so let’s look at some processes and strategies.
Refer back to the testing pyramid
The testing pyramid is a framework that provides reason and guidance on the different types of software tests and how to begin prioritizing between them. For example, it states developers should prioritize securing more significant numbers of unit tests, a typically cheaper and faster process due to their lack of reliance on external dependencies.
However, these unit tests don’t resemble the genuine actions of a real user with the application, which is why they must be supplemented by a range of minor integration, UI, and end-to-end tests.
These additional tests may make the process more cumbersome and slower to run, but they offer a more fully realized and realistic picture of the application and its usage.
Pick the right tools
Once you’re comfortable with the testing pyramid and your approach to testing data management (including its automated testing ROI), it’s time to select the right tools for the job.
There are several test data management tools on the market, each of which has its differing aspects, prices, learning curve, and resources. Selecting the right tool for an organization is a highly involved process that demands you learn the style of test data management that makes sense for your organization.
Tools involved in this process include extracting data subsets, conducting tool comparisons, and refreshing software back to its original state.
Common test data management challenges
Development teams require fast, reliable test data for their various products, a time-tight process that throws up many speed, quality, and security challenges.
Here are some of the most common challenges when managing test data:
- Test environment provisioning can be a slow, manual process: Developing a copy of test data takes significant time and effort. It can be an arduous process to get provisions updated for a test environment. The number of people involved in the process can strain the operation and create time sinks in the test cycle, slowing its overall pace.
- A lack of high-fidelity data: Development teams often lack access to test data fit for purpose. This can result in lost productivity due to time spent resolving data-related issues and increasing the risk of defects escaping into production.
- Privacy and safety compliance: Serious concerns in an age of compromised data, frequent information sharing, and lackluster storage managed by remote teams can lead to personal data used within these tests leaking, leading to significant reputational damage.
- Relying on outdated test data: Data that is no longer valid or up to date can limit new developments within your software and invalidate the testing processes with inaccuracies.
- Collaborative data corruption: Test data corruption can occur when the same test data is available to and used by different test teams.
Test data management is far from easy. Pitfalls and challenges are expected when developing sufficient test data and managing the faults of new software.
When developing your test data management strategy, consider the organizations that rely on your software and the everyday challenges they’ll encounter that require rigorous testing. To return to our remote working example, the rising reliance on software to support large-scale customer and industry support operations, such as remote enterprise call center software, raises the need for test data management to be a speedier, fool-proof process that doesn’t lean on low-quality data.
Maintaining a thriving test environment
With test environments proving so challenging, it’s essential to develop the maintenance and standardization.
Anyone within the industry will tell you how much time a tester can lose to issues with the environment or setup.
Considering the rapid increase in operating systems and the range of hardware and software we’ve seen in recent years, testing environments need to be dynamic and cope with significant alterations and needs on the fly. Test teams can ensure they are delivering a high-quality product with a good test management process.
Curating suitable test environments should be a priority for every test team.
Each release cycle brings a whole host of new challenges, which must be combated with revolutionary dedicated test data management environments that establish particular frameworks for effective maintenance and a smooth release cycle. As a result, test data management and what’s important in it are ever-changing.
Improving testing has several obvious benefits for organizations, from providing a cost-effective solution to enhancing product reliability.
About the Author
Jenna Bunnell is the Senior Manager for Content Marketing at Dialpad, an AI-incorporated contact center systems and cloud-hosted unified communications system that provides valuable call details for business owners and sales representatives. She is driven and passionate about communicating a brand’s design sensibility and visualizing how content can be presented creatively and comprehensively. Jenna Bunnell also published articles for domains such as Attention Insight and Agency Vista. Check out her LinkedIn profile.