5 Reasons Synthetic Test Data is better Than Real Test Data

Before rolling out any software or technological solution, it is imperative to test it. Once rolled out, the cost of fixing bugs and errors becomes significant. This is why test data has become all the more important factors in the testing of software. With the right test data and relevant data values, you can analyze the behavior and response of a system which helps you figure out the further course of action. In the absence of quality test data, software testing is not possible.

With new laws and regulations such as GDPR, the availability of test data has become more difficult. In the past enterprises found it easy to use real data for testing purposes because it depicted real challenges and real values. However, data and privacy protection policies in many regions of the world have made synthetic data generation obligatory.  There are various concerns regarding synthetic test data generation. Synthetic data generators must produce data that is new, complete, and valid. It should be properly masked to hide personal information. Synthetic data should adhere to the data privacy policy. The synthetic data generator should be able to generate and populate more data if there arises a need.

In this blog, we have laid out 5 reasons synthetic test data is better than real data.

1. Data Generation and Disposing Off is Quicker

U adopt for test data generation, make sure that it allows speedy generation of the data. During the testing phase, you don’t want to lag just because your approach is slow. Normally synthetic data generators allow quick data generation because they generate data themselves, and do not rely on other systems. Furthermore, getting rid of synthetic data is also easy. The moment information is no longer required; you can dump it anywhere because. Being synthetic data, there is no one’s information is compromised. As you are not violating any security concern, you can dispose of this data anywhere. On the other hand, disposing of real data becomes quite a task in itself. You have to figure out a way to dispose of this information so that it cannot be accessed by unauthorized entities.

2. Synthetic data generation costs less

Who would want to spend more on something that can be achieved with a lesser cost? Low cost is another parameter that should help you determine the solution for any purpose. When choosing any strategy, make sure you pick the one which is cost-effective so that it offers more ROI.

With real data, you have to acquire the data and then invest more resources in masking it. This increases the overall cost. On the other hand, synthetic data generators produce and mask data in one go- which eliminates the cost of masking. Keeping the cost factor in mind, synthetic data generators are a better deal as they help keep costs minimum.

3. High-quality generators produce quality data

There are many approaches to getting good test data. However, it is important to pick an approach that ensures that the data’s integrity remains intact; it is relevant and valid data. Sometimes, the real data is stale and quality assurance teams cannot perform successful testing because of this limitation. Synthetic data generators always produce relevant and fresh data. This is a surefire sign that you can use this data for effective testing. Good synthetic data generators produce reliable, relevant, and valid data.

4. Synthetic data ensures the privacy and safety of data

Above all the reasons to pick a synthetic data generator over real data resources, this one is the topmost reason. Real data compromises the safety, security, and privacy of entities whose data is being used. It is real data. Even though it is new or old, sensitive or general; real data does compromise the privacy of parties whose data is in use. Even stale or disposed of data is capable of causing some level of harm. Even masking can sometimes fail and give access to real information. Therefore, to avoid any legal complications or violating any regulations, we recommend using synthetic test data. It is synthetic- whose privacy is it going to breach?

5. Ease of Use and accessibility with synthetic data

Another reason for preferring synthetic data over real data is the fact that there are no complications involved. Synthetic data generators produce data as per requirements, and insufficient amounts. On the other hand, sometimes there is more than one source for obtaining the real data. At times, only authorized personnel can access this test data. This poses avoidable delays as well as complications.

Conclusion

Test data generation is a mandatory requirement during the development of software or IT solutions. There are many approaches to generating test data. However, synthetic test data generators produce good quality data that does not violate any privacy regulations.

GenRocket provides high-quality IT solutions. Being experienced in the industry, we know how to give desired solutions within minimum time and cost. to know more about our services and solutions, visit our website.

Leave a Reply

Your email address will not be published.