Testing & QA

Test data management is a complex task, particularly in enterprise environments filled with legacy systems, outdated databases, and deeply integrated components. Most organizations today rely on one of two main strategies to generate test data: using production data or creating mock data with predefined rules.

Using production data may provide a sense of realism, but it carries significant privacy and compliance risks. Many organizations attempt to mitigate these risks through anonymization or simple de-identification. However, these traditional approaches are often insufficient and can expose companies to regulatory and reputational consequences.

Rule-based mock data offers a safer path from a privacy perspective. It is widely used, especially when teams need to generate test data quickly. Still, it has practical limitations. Test engineers may not have full visibility into data schemas, and defining comprehensive rules to match real-world complexity can be time-consuming. The resulting data may lack the richness and variability of actual production environments.

Recent advancements have introduced AI-generated mock data as a valuable addition to the toolkit. While it does not automatically learn from existing datasets, it can assist in generating structured, schema-compliant test data that better reflects expected formats and business logic. This approach helps reduce manual rule creation and increases the relevance of mock data for common testing scenarios.

When combined with synthetic test data, which preserves the statistical properties of real data while eliminating sensitive information, organizations gain a more complete and secure foundation for testing. Together, synthetic data and AI-generated mock data support faster development cycles, improved test coverage, and full compliance with data privacy requirements.

Synthetic test data offers a wide range of benefits for modern software development. The MOSTLY AI Data Intelligence Platform empowers test engineers to generate realistic synthetic versions of customer data quickly and efficiently. By leveraging advanced generative AI models, the platform learns the structure, relationships, and business logic of the original data, then recreates it using entirely new, artificial data points. The synthetic data looks and behaves like the real thing but contains no connection to actual individuals.

This approach works seamlessly for both single-table datasets and complex multi-table environments, including relational databases. It preserves referential integrity and maintains the consistency of dependencies across tables, allowing for robust and accurate testing in realistic scenarios.

Because synthetic test data is fully anonymous, it is exempt from data privacy regulations. As a result, it can be safely used in non-production environments and even shared outside the walls of highly regulated institutions such as banks, insurance companies, or healthcare providers.

With synthetic test data, software testing becomes faster, more cost-effective, and significantly more secure. Most importantly, it helps teams deliver higher-quality products with fewer bugs and better user experiences.

While synthetic data brings powerful advantages to modern data-driven workflows, it is equally important to recognize its limitations and the responsibility that comes with using it effectively. The value of synthetic data depends on how well it captures the complexity, structure, and statistical nuances of real-world datasets. Only when these elements are faithfully replicated can teams rely on synthetic data for meaningful testing, development, and analysis.

At MOSTLY AI, we are committed to delivering the highest quality synthetic data on the market. Accuracy is at the core of our mission. The MOSTLY AI Data Intelligence Platform is built to generate data that mirrors real-world patterns with exceptional precision. Our proprietary generative AI technology ensures that even the most intricate relationships and distributions are preserved, enabling teams to make confident, insight-driven decisions based on synthetic data.

See the difference for yourself by starting to work with our Platform for free here. Experience how MOSTLY AI is setting the standard for accuracy in synthetic data and powering the next generation of safe, scalable, and compliant test data generation.