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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM41620

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

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM41620

Volume:

9 |

2 |

Feb 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM41620

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

BRK

Brahma Reddy Katam

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Abstract

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

Cite This Article

Brahma Reddy Katam, "Revolutionizing Data Accessibility: AI-Driven Natural Language Interfaces for Democratizing Data Discovery," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 2, Feb 2025. https://doi.org/10.55041/IJSREM41620

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Publication Date

2/17/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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