International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Augmented Analytical Dashboard |
|---|---|
| ABSTRACT | Contemporary business intelligence (BI) dashboards mainly center on data presentation and visualization, but they tend to require considerable manual analysis and are aimed at users with a technical background. This project addresses this issue by providing an Augmented Analytical Dashboard utilizing techniques of Artificial Intelligence (AI) and Machine Learning (ML) which are leveraged to additionally provide automated, actionable insights. Users will be able to log into the platform, upload a dataset, apply filters, visualize a dataset, and obtain automated interpretations of data and support for decision-making. In this way, data analysis is democratized allowing non-technical business users to approach data. |
| AUTHOR | NETRA CHANDRAKANT NEMAN, SAMIKSHA RAKESH PATIL, DISHA GANESH GAWADE, PROF. VIJAY SHANKER, PROF. JUNAID MANDVIWALA |
| PUBLICATION DATE | 2025-10-18 |
| VOLUME | 175 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1310018 |
| pdf/18_Augmented Analytical Dashboard.pdf | |
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