Why Is Test Data Management So Important?
by Carlos Schults
*Updated May 23rd 2022
Test data management is vital for achieving a healthy test automation strategy, yet many professionals are still not familiar with the term. They don’t know what the concept means, nor why it’s so important. But why would that be a problem? The technology world changes and evolves so fast that it’s hard to keep up. In order to stay alive in this frenetic environment, software development organizations have to change and evolve rapidly as well. They do that by adopting new tools, techniques, methods, and processes. Concepts like DevOps, agile, and continuous deployment belong to this trend. And so does test automation. Test automation processes require test data, which you need to obtain and manage.
That’s the role of test data management. But since so many are unfamiliar with the concept, they’re not able to reap its benefits and take their test automation strategies to their fullest potential. This post is our attempt at fixing that.
We start by showing why good test data is so essential for testing, following that with the reason you can’t just manage test data manually, which leads us to explore how test data management can improve that process. We proceed to define the term, and then we talk about its importance in three critical aspects.
The Need for Test Data Management
It makes sense to talk about the problem before we get to the solution. Why would you need test data management? What problems does it intend to solve? What are the benefits you’ll get from adopting it? Keep reading to learn the answers to those questions.
Garbage In, Garbage Out
Find the best woodworker in the world, give them some awful wood, and ask them to make you a dinner table. The result is likely to be subpar. It doesn’t matter how good of a system, process, or methodology you have. If you feed it with bad input (bad test data), the output is bound to be equally bad.
If you apply the same reasoning for testing, it becomes clear that quality test data is crucial. It won’t matter a bit how effective your test process is if you feed it bad data. All of the investment put into your test automation strategy will have been in vain if you don’t care for the quality of your test data.
The Force Will Always Be With You, Luke. But What About Your Test Data?
Ensuring quality, even though it’s a daunting task by itself, is only half of the challenge. As important as it is, quality won’t matter a bit if the test data isn’t there when you need it. That’s another responsibility of TDM: to ensure test data availability.
It’s useless to know that great test data exists when it’s not available for you to use. It’s probably even worse to have faulty data, readily at hand. We’re not willing to compromise here; we want to have our cake and eat it too. Let’s settle for high-quality data, with high availability. That’s what we can get through test data management.
Manual Data Test Management? Don’t Think So
You might be wondering, “Why can’t we just handle test data manually?” Well, while you can, in theory, we really don’t recommend doing so. First, you have the obvious downsides: it’d be a slow, error-prone process. But then you have some serious, not-as-obvious downsides.
To give a brief example, let’s consider one of the typical ways of obtaining test data manually: namely, replicating it from production. As the name implies, this technique consists of copying production data from production in order to feed it to the test process. Yes, your results will be as realistic as they can get; you’ve obtained it from production, after all. But on the other hand, you run the risk of exposing customers’ sensitive data i.e. PII (Personally Identifiable Information).
There’s also the risk of breaking the law. Depending on where you are in the world, there are already laws and regulations you must follow when it comes to protecting customer privacy. Is it worth all that risk just to avoid employing a proper TDM solution?
Test Data Management: What Does That Mean?
In the previous section, we’ve laid out some important points that show the need for a sane strategy for obtaining and managing test data. Our answer to that problem is, unsurprisingly, test data management. Let’s now present our own definition of the term, so we can progress:
Test data management (TDM) is the process of obtaining and administrating the test data needed for test automation processes, with minimal human intervention. As part of Test Data Preparation, TDM must ensure not only the quality of the test data, production data likeness, but also its availability.
As you can see, the definition above solves each one of the problems listed in the previous section.
Test Data Management Is Crucial
There are two main points we hope we’ve managed to convince you of by now:
- The quality of the data you feed your tests is as important—or maybe even more important—than the test process itself.
- You can’t ensure that quality by managing test data by hand.
- The logical conclusion is that you need to automate the way you handle test data, and that is what test data management is all about.
What we’ve covered so far is already enough to give you an idea about the importance of test data management. After all, if the quality of test data is super important, the process that helps achieve said quality is equally as important.
But we’re not claiming that TDM is just “important.” We claim that it is crucial, and to back such a claim, we need to go deeper. In the next section, we’re going to cover the specifics of why TDM matters by exploring three broad areas and explaining the benefits TDM provides to each one of them.
Why TDM Matters for IT Speed Delivery
As we’ve said in the introduction of this post, the software world changes so fast that it’s hard for companies to remain competitive. In order to survive, they have to be fast: not only at adopting new trends—and not adopting them, when it makes sense not to—but also at delivering their core products and/or services.
Trends like DevOps and continuous delivery come to mind. In the modern software landscape, it’s just not enough to release software monthly or even weekly. The larger and most successful companies deploy several times a day. But at such a frenetic deployment pace, how do you ensure the quality of each version? You’ve guessed it: test automation.
While there’s still a time and a place for manual testing, it is only through a solid test automation strategy that you can get to the highest levels of confidence regarding your app’s quality. What you don’t want is for your test automation process to get in the way of releasing software. But it will if it has to wait for the data it needs.
That’s why TDM is crucial for speed. As you’ve seen in the definition we presented two sections ago, test data management isn’t only about quality but also availability. One of its responsibilities is to make sure the data is where it’s needed when it’s needed.
Why TDM Matters for Quality
This point should be very clear by now. It’s simple logic:
- Test automation is required for a high-quality software testing and software output.
- A healthy software testing and test automation strategy require valid test data that has high quality and high availability.
- Test data management allows us to create test data, ensures both the quality and availability of test data, and ensures production data likeness.
- Thus, TDM is crucial for quality.
Quality without speed is useless. If you can deliver your services fast, you can bet your competitors will do it as well. On the other hand, speed without quality is catastrophic. That’s why you need both, and test data management can provide that for you.
Why TDM Matters for Compliance
Finally, we get to compliance. For starters, what does that mean? The CASRAI dictionary defines it as follows:
Data compliance consists of the ongoing processes to ensure adherence of data (including test data) to both enterprise business rules (government department, university, industry, or agency), and legal, regulatory, and accreditation requirements.
In a nutshell, compliance means making sure your data adhere to data security regulations, which can be both internal (business rules) and external (i.e., laws and regulations). So, what does testing has to do with compliance? Well, everything.
In order to effectively test when developing your services, you need “production-like” data. That introduces a serious challenge, though, since organizations are responsible for their client’s data, ensuring it’s protected from misuse or disclosure. Failing to comply with privacy acts (e.g., GDPR) brings serious financial and legal consequences, not to mention the damage to the company’s reputation.
How can test data management help you with that? By employing a mature TDM and data compliance tool, you gain the ability to easily and quickly mask data, sipporting data security objectives, as well as the ability to perform compliance analysis and generate reports.
If you choose not to employ a tool, then you can only resort to manual test data preparation procedures. For instance, you can rely on custom scripts to perform the data masking, which will result in the expected problems common to manual approaches: slowness, high probability of errors, and so on.
Back to You
Test data automation is definitely a hot topic in the software world nowadays. With each passing year, more and more software organizations adopt it. Many tech conferences around the world have entire tracks dedicated to the subject. The number of books on automated testing and test automation is also enormous, not to mention the blog posts and white papers written on it. Academia is also interested in the topic, as the number of articles that mention it demonstrates.
All of that interest doesn’t mean it’s all a bed of roses when it comes to test automation. Teams and organizations still make a lot of mistakes. Individuals have misconceptions about testing and fall prey to anti-patterns. There are still many important challenges to overcome. For instance, providing good data for testing continues to be an Achilles’ heel in the process.
Test data management aims to change that by ensuring that you can consistently prepare test data, have the right test data, realistic test data, and ensure data security to avoid a data breach. When it comes to data security and compliance, TDM is also able to help you, giving you the means to make sure your test data adheres to all the necessary laws and regulations and ensure your sensitive data does is not vulnerable to data breaches.
If your company isn’t reaping the benefits of TDM, now is a great time to start doing so. Use this post as a starting point for your studies, but don’t stop here. Now that you have a basic general knowledge of test data management, the next step is to go deeper. Research and discover the TDM tools available and give them a try. Read more, not only about test data management but also about test automation in general. Use the knowledge and experience you acquired to improve your test automation approach, rinse, and repeat. In short: learn TDM, put it to good use, and you won’t regret doing so.
Thanks for reading, and until next time!
Test Data Next Steps
Looking to address the needs of Test Data Management? Looking to bolster your current Data Security Solutions? Why not ask us about Enov8 Test Data Manager, our DataSec & DataOps solution.
A platform that uses automated intelligence to identify where data security exposures reside, rapidly remediate these risks without error (production data masking), and centrally validate your compliance success. The solution also comes with IT delivery accelerators. Including a Fabricator to create test data (synthetic data), DataView for Data Mining, Test Data Booking Management capability & a DataOps Library for automation.
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This post was written by Carlos Schults. Carlos is a .NET software developer with experience in both desktop and web development, and he’s now trying his hand at mobile. He has a passion for writing clean and concise code, and he’s interested in practices that help you improve app health, such as code review, automated testing, and continuous build.
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