Test Data That Scales With Your Business
As enterprise data grows ever-larger and more complex, a scalable test data solution must produce data rapidly for integrated technologies. To help deliver quality software at speed, it must create high volumes of data on demand, supporting data-intensive activities like stress testing.
Test Data Automation is a high-performance, lightweight solution, offering easy scalability without demanding heavy infrastructure. A default configuration is capable of generating millions of rows of data in minutes, accelerated by load balancing, multi-threading, horizontal scalability, and more.
Can you automate as quickly as EVERFI?
A Range of Performance Enhancing Techniques
Curiosity have built Test Data Automation using modern technologies and principles, differentiating it from decades-old tools that have been inconsistently modernised. A range of technologies and techniques ensure Test Data Automation’s scalability, resource-efficiency, and performance:
Test Data Automation jobs run at speed across distributed resources, including the option of multi-server deployment.
Parallel processing accelerates test data creation, with multi-threading to create all the data you need.
A lightweight, private or hybrid cloud deployment approach provides browser-based access, with easy scalability.
Deploying on Docker and Kubernetes allows easy upgrades, horizontal scalability, and sharding for optimal performance.
A jobs queue and “hopper” automatically submit jobs to Test Data Automation’s server, running jobs in parallel for optimal performance.
The Data You Need, When You Need it
These performance-enhancing techniques ensure that Test Data Automation’s integrated data activities run rapidly and affordably, resolving “just in time” to provide accurate data during testing, development and CI/CD.
Leveraging this complete toolkit doesn’t just create high-volumes of data. It ensures that on demand data is concise and capable of delivering quality software, faster. Data produced by Test Data Automation is:
A range of analysis techniques allow you to understand your data and identify coverage gaps. Data generation, cloning and data flow modelling then create all the data needed for rapid development and rigorous testing.
Data profiling, masking and synthetic data generation with Test Data Automation finds and removes sensitive data from non-production environments, reducing the risk of data breaches and costly non-compliance events.