Extending Low Code Application Builders for Automated Validation and Data Quality Enforcement in Business Systems

Abstract

This article investigates how extending low-code application builders with automated, rule-driven
validation mechanisms enhances data quality, system reliability, and governance across enterprise business
applications. By incorporating metadata-driven rule engines, reusable validation components, and real-time
enforcement layers, low-code platforms significantly reduce data errors, improve validation throughput, and
maintain consistency across diverse workflows and integration points. Experimental results demonstrate
substantial gains in accuracy and runtime efficiency, while governance mechanisms ensure traceability,
compliance, and uniform policy enforcement. These findings position automated validation as a critical
advancement for scaling low-code adoption within mission-critical enterprise ecosystems.
Keywords---data validation, low-code platforms, data quality enforcement