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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM44993
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
In today’s data-driven world, businesses and analysts face significant challenges in extracting actionable insights from large datasets, particularly CSV files, without advanced technical expertise. AutoStream addresses this gap by offering an intuitive, local-first platform designed to empower users of all skill levels. By simplifying data exploration, the platform allows seamless uploading of CSV files, automatic generation of key insights, and interactive visualization tools for in-depth analysis — all without writing a single line of code.Built with user-centric design and extensibility in mind, AutoStream eliminates the complexities of manual data processing and empowers faster, smarter decision-making. Features like natural language data querying (powered by Mistral + PandasAI), one-click EDA reports (via Sweetviz), AutoML capabilities (with PyCaret), and SHAP-based explainability tools help users navigate their data with ease and confidence.With everything running securely on the user’s local machine, Auto Stream is ideal for sensitive or enterprise environments where privacy is paramount. This innovative platform not only saves time but also bridges the gap between raw data and strategic insight. Would you like further refinements or to expand it?
KEYWORDS
Publication Date
4/20/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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