Revolutionizing Data Accessibility: AI-Driven Natural Language Interfaces for Democratizing Data Discovery

作者：Brahma Reddy Katam · 发表于：INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · 年份：2025 · DOI：10.55041/ijsrem41620 · 被引用次数：1

We live in an era where data fuels everything—from business decisions and healthcare innovations to government policies and financial markets. Yet, a vast majority of professionals, the very people who need this data the most, struggle to access it because of technical barriers. Data isn’t just sitting there; it’s locked away behind SQL queries, complex BI dashboards, and intimidating APIs. This paper explores how we can break down these barriers and build truly user-friendly data access tools for non-technical users. We introduce a novel framework that combines AI-powered natural language queries, intelligent search recommendations, and interactive visualizations, making data as easy to explore as searching for something on Google. Through real-world usability tests, we found that task completion efficiency improved by 78%, while dependency on IT support decreased by 41%. By making data discovery intuitive, we’re not just helping businesses move faster—we’re enabling more people to make data-driven decisions without writing a single line of code. Keywords: Data Accessibility, Natural Language Query, Human-Centered AI, Data Discovery, User Experience (UX), Cognitive Computing