Smart Data Hub: Comprehensive Tool for Visualization, Mining, Cleaning & Prediction
Abstract
The exponential growth of data has led to an increased demand for platforms that streamline data processing and analysis. Smart Data HUB is a comprehensive solution that integrates data visualization, data mining, data cleaning, and predictive analysis in a unified system. This paper presents the architecture, implementation, and key functionalities of Smart Data HUB. The platform enables users to upload files in various formats (XML, CSV, Word, Text) and apply multiple data processing techniques efficiently. The experimental results indicate that the system enhances workflow efficiency by reducing manual effort and improving accuracy in data-driven decision-making.
References
. V. Restat, M. Klettke, and U. St¨orl, “Towards an end-to-end data quality opti-
mizer,” in 2024 IEEE 40th International Conference on Data Engineering Work-
shops (ICDEW). IEEE, 2024.
S. Agarwal, “Data mining: Data mining concepts and techniques,” in 2013 Inter-
national Conference on Machine Intelligence and Research Advancement. IEEE,
Devidas S Thosar, Rajashree R Shinde, Prashant J Gadakh, Pratibha V Kashid, Secure kNN Query Processing in Entrusted Cloud Environments , Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, Issue I , Vol 2 (2016).
X. Ding et al., “Time series data cleaning under expressive constraints on both rows
and columns,” in 2024 IEEE 40th International Conference on Data Engineering
(ICDE). IEEE, 2024.
Devidas S. Thosar*, Dr. Nisarg Gandhewar. (2022). An advanced image authentication using passimage algorithm to resist shoulder surfing attack. Computer Integrated Manufacturing Systems, 28(10), 52–59.
T. Nirusanan et al., “Refining large language models for tabular data analysis in
business domain by laymen text,” in 2024 International Research Conference on
Smart Computing and Systems Engineering (SCSE), vol. 7. IEEE, 2024.
H. Cao, M. Yin, and Y. Xi, “Data-mining of social media users with embedding
techniques and neural network,” in 2024 IEEE 6th Advanced Information Manage-
ment, Communicates, Electronic and Automation Control Conference (IMCEC),
vol. 6. IEEE, 2024.
S. Guha et al., “Automated data cleaning can hurt fairness in machine learning-
based decision making,” IEEE Transactions on Knowledge and Data Engineering,
D. S. Thosar and M. Singh, "A Review on Advanced Graphical Authentication to Resist Shoulder Surfing Attack," 2018 International Conference on Advanced Computation and Telecommunication (ICACAT), Bhopal, India, 2018, pp. 1-3, doi: 10.1109/ICACAT.2018.8933699.
Pagare, Snehal, Devidas S. Thosar and Kishor Shegde. “Agriculture Food Supply Chain Management using Blockchain Technology.” (2021) in International Research Journal of Engineering and Technology (IRJET), e-ISSN: 2395-0056, p-ISSN: 2395-0072, Volume: 08 Issue: 03 | Mar 2021
Refbacks
- There are currently no refbacks.