Datasmart : Enhancing College Administration with a Web-Based Database Management System
Prof. Shailendra W. Shende1,
Assistant Professor, Department of Computer Science and Engineering, Government College of
Engineering Chandrapur, Maharashtra, India
Megha Shil2, Kunal Joshi3, Mahesh Rampure4, Prajwal Taksande5, Sejal Sahare6
23456, Final year student, Department of computer science and engineering, Government College of Engineering, Chandrapur, Maharashtra, India.
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Abstract –
The DataSmart: College Data Management System is an advanced desktop application designed to optimize academic and administrative data handling in educational institutions. Traditional methods for retrieving and managing college data are often inefficient, fragmented, and prone to errors, leading to inconsistencies and delays. DataSmart overcomes these challenges by integrating AI-powered natural language processing (NLP), which converts user queries into SQL for seamless data retrieval. Additionally, blockchain technology ensures the confidentiality, integrity, and traceability of academic records, enhancing security. The system features an intuitive user interface, allowing faculty, administrators, and students to efficiently access, analyze, and manage institutional data. It supports multi-format data exports (CSV, Excel, PDF) and provides advanced data visualization tools, offering insights through interactive charts and graphs. Designed for seamless integration with existing databases, DataSmart maintains real-time data synchronization and consistency. This paper discusses the system’s architecture, key functionalities, and technological innovations, demonstrating its potential to revolutionize data-driven decision-making in academic environments. By improving efficiency, accuracy, and security, DataSmart transforms how educational institutions manage and utilize administrative data, ultimately enhancing workflow and user experience.
Keywords: College data management, AI-powered search, Blockchain security, Natural language to SQL (NL2SQL), Data visualization, Academic data retrieval, Secure data storage, Educational technology, Institutional data analytics.
