Test data: Path Ahead

The world Quality reports clearly mentioned unhappiness over the progress made on Test data and Test environment management in the year 2019. The biggest obstacle to progress in testing is Test Data. 60% of the projects still using spreadsheets to manually generate new test data. The secret to quality at speed lies at the intersection of three technologies CI/CD Pipeline, Test Automation, and Test Data provisioning. We shall focus on ever-increasing challenges faced with managing test data and the paradigm shift from traditional Test Data Management (TDM) to new age Synthetic Test Data Generation (TDG).

Challenge 1: Test Data procurement

Digital enterprises facing a lot of challenges for testing their application. Looking at current data privacy policies, moving data from production is very much challenging. On one hand, there are data privacy challenges and on the other hand, the business required the most realistic data for testing.

Challenge 2: Test Data ownership

Generating test data manually is a very time-consuming job. As per one of the reports, 64% corporates use manual methods to generate test data, and 34% clone the production data and cleansing it. Only 2% use other methods for test data generation. It is always debatable who owns the test data. Is it the responsibility of the tester to procure, maintain and preserve test data, or it the job of the environment team? Question unanswered.

Challenge 3: Test data for continuous testing

85% of QA organizations have introduced Test automation into their operations to reduce manual testing efforts. The approach of provisioning test data is traditional TDM approach, which is cumbersome, complex, and costly.

What are the possible solutions to the challenges?

A. Test Data Generation

Test Data Generation (TDG) is a modern alternative to the traditional Test Data Management (TDM) approach and manual creation. It provides synthetic data in place of the Personally Identifiable Information (PII) found in production data. These tools comprise a fully integrated environment that enables full-scale deployment of test automation across the QA organization and throughout the continuous delivery development cycle. TDG is the future for Quality Intelligence.

B. Test Data Automation

Test data Automation is an amalgamation of Test data generation and Test data management. In real life, you cannot fully rely on the afresh generated test data nor a production cut. Test data automation follows the systematic process of Test data procurement. It collects master data through TDM. Generate transaction data through TDG. Build a co-relation between master and Transaction data using complex business logic. The process sounds tedious but robust.

C. Setting up test data COE

An intelligent automation framework provisions its own test data. The large scale enterprises should set up the Centre of Excellence (COE) for test data provisioning. This team should keep an up-to-date copy of the production data. The team should engage in,

  • Copying, subsetting and retaining useful copies of production data
  • Masking data for security purposes and managing test data set versions
  • Maintaining data quality and consistency across multiple test operations

Conclusion

There is no silver bullet to solve all the test related issues. SDET and QA team should work with various stakeholders like Product owners, Developers, Architect, IT, and Data security teams to ensure the best suitable solution for your organization. However, Test data automation is a promising option. IVL Global is a partner with GenRocket. GenRocket is the leader in real-time synthetic Test Data Generation (TDG), high-performance technology for provisioning test data at the speed of development. We build Test data automation solutions for our enterprise customers. It gives IVL an advance to be ahead of curve on the technology stack.