As a company grows, their data keeps increasing. Merely storing it in a database won’t do you any good. Your testers may face problems while trying to access any test data from a huge database. To help your business thrive, you must adopt a sound test data management (TDM) strategy. And to do that, you need to understand how test data management works.
TDM can be challenging for a QA team as there are so many factors to consider. So in this post, we’re going to discuss how test data management works. This detailed guide will tell you what TDM is and other relevant details. We’ll check out different TDM techniques and challenges and discover how to overcome them using best practices.
So, let’s dive into the details.
What Is Test Data Management?
Data can include both information that has yet to undergo analysis as well as information that a user is unsure where to implement. But when this data is for testing software applications, we call it test data. Test data management is a method that testing teams use to satisfy test data requirements. TDM involves creating nonproduction data sets to imitate a firm’s real data. This process enables developers to perform valid and rigorous system tests. TDM is also a crucial part of the software testing life cycle (STLC). Wondering why? Let’s find out in the next section.
Why Is Test Data Management Important?
Gone are the days when just advertising your business did all the work for you! So, now you must be thinking, what should I do to make my firm flourish? The answer is simple. To survive in today’s competitive world, you must know how to steer the crowd toward your business. With so many companies out there, standing out might seem challenging at first. But you must realize that working differently from others is the only way you can make your business thrive in the long run.
As you make more attempts to stand out, the amount of data you generate increases. Test data sorting is a massive task and calls for proper management. Therefore, it’s important to have a sound test data management strategy. It helps curb the data problems most firms face today. For example, did you know that most development teams don’t have access to the required test data? This further drives the need for enhanced TDM.
TDM can also help in gathering data for testing. During app development, data lies in silos. But the question arises, how do you make this scattered data useful? The answer is test data management. This process includes using synthetic tools for generating data. Another important process is data masking. These techniques prevent you from using real users’ data for testing, thus complying with data regulation policies like GDPR. But are these two techniques enough? Or is there more to TDM? Let’s jump to the next section where we’ll discuss the different phases of test data management.
What Are the Different Steps of Test Data Management?
So now that you understand the why for test data management, let’s understand how test data management works! There are four main steps you need to follow for managing test data. Let’s take a look.
1. Exploring the Test Data
We know that data exists in different forms like text, media files, or XML. But the mere existence of data is not enough, is it? To use company data for improving business, teams first need to analyze test cases and what these test cases need. Based on that, they need to explore the correct data sets. Moreover, suppose you’re trying to locate the right data in the correct format. While doing so, you also have to keep the time constraint in mind. After all, you don’t have forever to keep searching for the right data sets!
Locating and retrieving data manually can be more tedious than you think. It can compromise the efficiency of the entire process. So, what’s the solution? Of course, we need a solution ensuring effective data visualization and coverage analysis. Establishing a killer TDM approach helps in exploring data sets and analyzing them further.
2. Validating Test Data
We live in a world where most firms work in the agile way. Do you realize what this means? Sourcing data from real end users isn’t a big deal since your team will be directly interacting with the clients. However, you have to be careful with sensitive user data such as names, addresses, financial information, etc. The security of this test data has to be a high-priority task. Moreover, as per data privacy regulations, you can’t use real data. So, how do you carry out testing?
Testing teams can use the data pattern and simulate synthetic data. This synthetic data resembles real user information that testers can use to test the app. Later, testers can mask the data for safeguarding the information. This way, before the app goes live, testers will finish executing all the test cases. That, too, while keeping the sensitive data secure.
3. Sorting Test Data for Reusability
Reusing data is your holy grail to minimizing test efforts. It also reduces the overall cost. Building and segmenting test data makes the data reusable. There should be a central database to access test data. While testing a feature, if you find that you can use the same data to generate new test cases or for testing another feature, sort it accordingly.
Making the data reusable improves the overall testing process. QA teams don’t need to waste time to find new data. For testing similar features, they can use reusable assets. You just need to do one thing. Before storing any data in the reusable category, validate it and make sure the data is reusable.
4. Accelerating TDM With Automation
TDM includes activities such as data generation, scripting, cloning, data masking, etc. Now, we know that automating these processes will make the activities quicker. But do you know how else automation will benefit TDM? It’ll increase the proficiency of different data processes. Feeding the test data into an automation tool ensures that the data is always available. For instance, whenever the QA team wants data, they can use the tool to fetch it, thereby reducing manual effort. This way, the QA team is able to save more time in the long run.
The overall process looks simple and sounds fun. But it also comes with some challenges. Let’s find out what those are.
Challenges of Test Data Management
Test data management includes a lot of different processes. As a result, it becomes a challenging task. Here are some common challenges firms face while implementing a TDM strategy. Let’s check them out.
1. Safety of Stored Data
Companies spend a lot of time developing test data. However, if you fail to ensure the safety of the data stored, all your efforts might be in vain. Data breaches can financially break a firm if not prevented. Therefore, choosing a safe data storage method is a must. Ensure that your firewalls and data security protocols are enough to keep data safe.
2. Test Data Sorting Complexity
Finding out relevant test data from a big database can prove to be a challenging job. If your project is huge, the database may be filled with lots of relevant as well as irrelevant data. What if the TDM process of your company is manual? Testers have to spend a lot of time sorting data for testing and sorting test data to find reusable data. The ideal solution in this scenario is to use an automated test data management suite.
3. Relevant Data Not Present During Testing
Even though there’s no shortage of data in a company, picking the relevant tidbits is a challenging task. Sometimes, companies can’t use real-time data due to compliance standards like GDPR. Instead, use a test data generation software. It’ll keep the data meaningful, realistic, and in compliance with standards. However, before using it, ensure that the software is reliable.
The challenges sound a bit complex. Scared? Well, don’t be. You can easily overcome these challenges if you follow some best practices. Let’s find out about these in the next section.
Overcome the Challenges With Best Practices
So now that you understand how test data management works in theory, it’s time to put it into practice.
To get the most out of your TDM efforts, here are some best practices you need to follow. They’ll also help you overcome the biggest TDM challenges. Let’s take a look.
1. Data Generation/Extraction
The foremost practice in TDM is to define what you need clearly. Consider the type of data you need and find out where it’s located. After that, figure out how to access the data. Also, keep in mind that you have to refresh the data to prevent it from becoming obsolete. Thus, you need to decide the frequency of refreshing the data.
2. Protect Sensitive Information
Every company database has loads of customer information. Since there’s a lot of personal data, protecting it is a key requirement. Data privacy regulations and laws are becoming stricter day by day. Thus, firms need to implement data masking and encryption techniques to protect customer data.
3. Plan to Use Data as Per Requirements
No firm can put all their data to use. Therefore, you need to have a plan about how to use the relevant data. This also helps in reducing the overhead that can incur during test environment management. Wondering how a plan reduces overhead? Let’s understand this with the help of an example.
Suppose your company is supporting a client with their customer database in Salesforce. There are about a few thousand units of customer data. But once you dive into the data and go through the details, you find out that almost 40% of these customers no longer use their accounts. Temporary deactivation of those user profiles makes your job easier. You can work with the existing customer data without the fear of getting lost in an endless database of customers. Just like that, in your company, archiving unused data reduces overhead.
4. Auditing the Data
Is your data set right for the defined purpose in your project? Also, are you sure that the data you’re using complies with data privacy and security regulations? Auditing the test data helps to answer these questions. Schedule a yearly data quality and security audit in your company. This will assure you that your data is secure and follows all data protection and privacy rules.
Empower Software Testing With TDM
In this post, you learned how test data management works and some best practices for it.
Application testing generates a huge amount of data. It’s important to process this data and generate reports that help in adding value to the software. TDM minimizes the time it takes for data processing and report generation. All in all, TDM streamlines the test data process by obtaining, enhancing, and securing the test data.
So, do you want to empower software testing in your company? If that’s the case, TDM is the way to go.
This post was written by Arnab Roy Chowdhury. Arnab is a UI developer by profession and a blogging enthusiast. He has strong expertise in the latest UI/UX trends, project methodologies, testing, and scripting.