Democratizing Data Access: How Mainframe Migrations Are Enabling Inclusive Analytics

• Published in: European Journal of Computer Science and Information Technology Vol. 13; no. 50; pp. 58 - 67
• Main Author: Khandelwal, Ashish Prakash
• Format: Journal Article
• Language: English
• Published: 26.06.2025
• ISSN: 2054-0957; 2054-0965
• DOI: 10.37745/ejcsit.2013/vol13n505867

This article examines how migrating mainframe database systems to cloud platforms fundamentally transforms organizational data accessibility. The transition from legacy systems to modern cloud environments such as Microsoft Azure SQL, Cosmos DB and Microsoft Fabric represents more than a technological upgrade, it constitutes a paradigm shift in data democratization, by removing technical barriers that previously limited data access to specialized personnel, organizations across healthcare, government, education, and other sectors are fostering more inclusive analytics capabilities. The article explores this transformation's social, organizational, and technical dimensions, highlighting how broader data access enables more diverse stakeholders to participate in decision-making processes, ultimately contributing to data equity and social empowerment. The democratization process dismantles longstanding information hierarchies that have historically concentrated analytical power within technical departments, replacing them with distributed access models that align with functional roles rather than technical expertise. This shift enables domain experts to directly engage with organizational data through intuitive interfaces, semantic abstractions, and self-service tools that require minimal technical knowledge while preserving analytical rigor. The resulting transformation extends beyond operational efficiencies to reshape organizational culture, power dynamics, and collaborative frameworks in ways that promote inclusive decision-making and expand the community of data participants.