Does it take a lot of time or manual work to get your test data right?
Getting test data right can be time-consuming and require manual effort, especially if the data needs to accurately reflect real-world conditions. In this video, we will explain how synthetic data works to save your time and manual work.
This video is captured from the Syntho webinar about why do organizations use synthetic data as test data?. Watch the full video here.
We conducted a survey to inquire whether people find it time-consuming and/or require manual efforts to obtain their test data right.
Importance of Accurate Test Data
When it comes to testing, having accurate test data is essential. Bad test data can lead to inaccurate results, which can ultimately harm your project or product. However, creating good test data can be a time-consuming and challenging task.
Manual Work Involved
According to Wim Kees, creating good test data can take a lot of manual work. This is especially true when it comes to creating synthetic data, where it can be difficult to account for all possible exceptions and patterns.
Professional testers understand the importance of accurate test data, whether it’s for manual or automated testing or even for synthetic test data. They put a lot of effort into ensuring that their test data is reliable and accurate.
Simplifying Test Data Efforts
The good news is that there are tools available that can help simplify the process of creating and using accurate test data. With trustful test data that is reusable and shareable, professional testers can save time and effort.
In summary, having accurate test data is crucial for successful testing, and professional testers should prioritize creating and using reliable test data. Using tools to simplify this process can make a significant difference in the efficiency and effectiveness of your testing efforts. Finally, it’s important to strive to minimize the use of personal data whenever possible for maximum benefits.
It is relevant to the topic of synthetic data as it highlights the challenges of creating good test data, especially in the context of synthetic data where accounting for all possible exceptions and patterns can be difficult. It also emphasizes the importance of accurate test data for successful testing, whether it is manual, automated, or synthetic testing. Moreover, it suggests that using tools to simplify the process of creating and using accurate test data can help professional testers save time and effort. What is important, we need to remember to prioritize privacy and strive to minimize the use of personal data whenever possible for maximum benefits.
We are experts in synthetic data. But, don’t worry, our team is real!
Contact Syntho and one of our experts will get in touch with you at the speed of light to explore the value of synthetic data!