DQV is the comprehensive data quality and testing platform developed by Kumaran Systems, catering to teams engaged in the movement, masking, or validation of substantial data volumes. This tool meticulously evaluates source and target datasets on a field-by-field basis, identifies discrepancies, and produces mismatch reports, eliminating the need for manual checks using spreadsheets.
The platform encompasses five key functionalities: it performs field-level comparisons while detecting drift, facilitates migration mapping between different schemas, offers deterministic PII masking, conducts record- and table-level validation with the ability for on-the-fly corrections, and generates synthetic data for teams lacking access to production data for testing.
DQV is compatible with a wide range of data sources, including SQL Server, Oracle, MySQL, PostgreSQL, AWS, Azure, GCP, flat files, JSON, XML, and REST APIs, and it seamlessly integrates with tools like Informatica, Databricks, and CI/CD pipelines, or can operate independently as a library or CLI tool.
In real-world applications, DQV has successfully validated an impressive 26.6 million bank records in less than 22 minutes, showcasing its efficiency and speed. Additionally, a free trial is offered, along with various licensing options, including individual, enterprise, and on-premises plans, ensuring flexibility for different organizational needs. This versatile solution not only enhances data integrity but also streamlines the testing process across multiple platforms.