Understanding GenRocket TDG
The Next Generation of Test Data Management
In this era of continuous testing and integration, much has been written about the need for accelerated test data provisioning. Test Data Management (TDM) systems are finding new ways to copy, subset, mask and refresh production data at a faster pace. However, even with incremental time savings, these test data management processes are a viscous circle that are quickly becoming outdated and obsolete.
Many TDM vendors offer some form of Test Data Generation (TDG) as a synthetic data alternative to the use of sensitive production data. However, it’s part of the same Test Data Management paradigm that requires a costly, complicated, monolithic platform to provision test data for today’s agile development environment.
GenRocket TDG – the Next Generation of TDM
GenRocket TDG is a fresh, new approach for provisioning secure, accurate, and controlled test data in high volume and on-demand. It’s the next generation of Test Data Management. GenRocket TDG creates any kind of test data on-the-fly, whenever it’s needed. There’s no gold copy test database to store and maintain. There’s no longer a need to mask or refresh test data sets. And there’s no extreme cost or complicated software to centrally manage. GenRocket replaces the cost and complexity of traditional Test Data Management with a low-cost, self-service paradigm for test data provisioning.
To understand GenRocket TDG, one must think differently about test data. Abandon the notion that all test data must either be copied from a production database or painfully created by hand in Excel spreadsheets.
The Test Data You Need, When You Need It
This diagram illustrates the GenRocket TDG paradigm in action. During the execution of an automated test case, there may be points during the test where (1) Database queries are needed to retrieve test data, (2) calculations are performed using test data, and (3) Updates to a database are blended with test data.
As an example, to test an online shopping cart transaction, a part-number lookup and item retrieval might be tested. This might be followed by a credit transaction to calculate the purchase price along with updates to the customer billing and inventory systems.
GenRocket can dynamically generate data for each stage of this automated test case in real-time, with complete control over the nature of the test data to be generated at each stage of the workflow. This example illustrates how GenRocket can streamline a comprehensive end-to-end testing process.
5 Guiding Principles of GenRocket TDG
Let’s have a closer look at the GenRocket TDG paradigm by understanding its 5 guiding principles.
1. SYNTHETIC DATA
GenRocket test data is 100% secure because it’s synthetic data generated to recreate sensitive production data like social security numbers, credit card account numbers, and medical procedure codes. Every day, GenRocket’s real-time synthetic test data is being used to test mission-critical applications in financial services, health care, ecommerce and other software-intensive industries. GenRocket’s modular platform includes hundreds of test data generators and receivers designed to produce any type of data in any file format. With GenRocket TDG, 90% of the production data used for testing can be replaced with synthetic test data, in a fraction of the data provisioning time.
GenRocket generates synthetic data by following the rules in a test data scenario, a precise definition of the data volume and variations required for a given test case. A test case may require positive and negative testing, edge case testing, or load testing with well-defined patterns and permutations of data in sufficient volume to maximize coverage or test application performance. With test data scenarios, the tester controls how test data is created to ensure the accuracy and completeness of testing. With production data, testing is limited to whatever is contained in the data subset. With GenRocket TDG, testing is only limited by the imagination of the tester.
GenRocket TDG follows the data model used by the production database to ensure test data is fully representational and realistic. GenRocket can use the data definition language for a given database or an imported database schema. GenRocket holds the only patent for generating synthetic test data with complete referential integrity, preserving parent-child-sibling relationships between key fields linking multiple data tables. GenRocket’s ability to replicate any database structure, combined with an ability to specify test data variation and volume, results in synthetic test data with higher quality than production data that has been copied and subsetted.
One of the more difficult concepts for QA professionals new to GenRocket TDG is the real-time nature of its data. A traditional Test Data Management environment involves managing a physical test database cloned from a production database that is masked and refreshed for each new test operation. GenRocket test data is dynamic – it’s only generated when needed and eliminated when it’s not needed. By generating test data at the rate of 10,000 rows per second (based on the processing power of an ordinary PC), GenRocket routinely accelerates test data provisioning by 1,000% or more.
GenRocket was designed from the ground up to be adaptable to any test environment. Its intelligent API allows test data scenarios to be invoked by external applications and test automation tools. This enables highly integrated and streamlined test operations. The GenRocket API makes any kind of test data instantly available during test procedures for complex workflows and sophisticated use cases. GenRocket also has the ability to blend synthetic data with production data to realize the best of both worlds. As a result, GenRocket makes it easy to perform comprehensive end-to-end testing for all forms of financial transactions, database interactions or computational operations.
Create. Generate. Validate.
The GenRocket TDG paradigm for Test Data Generation can be summarized by this simple phrase: Create. Generate. Validate. It represents the 3 basic steps any tester can perform to provision test data quickly, easily, cost-effectively and with complete control over test data variation and volume.
your test data requirements for variety and volume using a Test Data scenario
Real-Time synthetic test Data by invoking a test Data scenario during testing
Perform continuous Testing and Integration with full code coverage