Advanced methods for database query optimization in financial reporting systems

Posted: Apr 21, 2015

• Theodore Roberts
• Victoria Campbell
• Victoria Flores

Abstract

The exponential growth of financial data volume and complexity has placed unprecedented demands on database systems supporting financial reporting. Traditional query optimization techniques, while effective for general-purpose applications, often fail to address the unique challenges inherent in financial reporting environments. These systems must process complex analytical queries across massive datasets while maintaining strict compliance with regulatory requirements and delivering results within tight temporal constraints. This research addresses these challenges by developing a novel quantum-inspired optimization framework that fundamentally rethinks how query optimization should be approached in financial contexts. Rather than treating financial constraints as external factors to be accommodated after optimization, our framework integrates these constraints directly into the optimization process itself. This approach enables the generation of query execution plans that are not only computationally efficient but also inherently compliant with financial regulatory requirements and aligned with the temporal characteristics of financial data.