Student Data Integration and Consolidation System

Nishith Khandor*, Dhruv Mehta**, Zirak Mistry***, Ayush Mittal****, Sagar Korde*****
*-***** K.J. Somaiya College of Engineering, Mumbai, Maharashtra, India.
Periodicity:April - June'2019
DOI : https://doi.org/10.26634/jse.13.4.15934

Abstract

With the advent of Information Technology in today’s time, there is no dearth of increasing requirements for storing and retrieving data. As the data produced per year increases at an explosive rate, storing this data and representing it in a well-structured format and in a timely manner is one of the biggest issues today for the organizations and institutions. This paper proposes an approach to manage and access large amounts of distributed unstructured data of an organization in an efficient manner. Hence, a web-application has been designed to efficiently access and manage the data and to save precious time spent in accessing the distributed data. This system also makes an attempt to solve the problem of data availability and data accessibility, both of which are very important from an organization’s point of view that works with data on a day-to-day basis. Data security for organizations is very important and hence the system also incorporates a security feature with the help of the SSL technology which will ensure that data transfer remains private and integral over the internet during the client and server communication. Also the paper proposes the methodology which describes the basic features provided by the web-application along with a set of special features that can help reduce effort and provide useful analysis and data visualization based on the data of the organization.

Keywords

Unstructured Data, Nosql, Python, Distributed, Excel, Upload, Mongo Db.

How to Cite this Article?

Khandor, N., Dhruv, M., Mistry, Z., Mittal, A., & Korde, S. (2019). Student Data Integration and Consolidation System. i-manager's Journal on Software Engineering, 13(4), 24-33. https://doi.org/10.26634/jse.13.4.15934

References

[1]. Babu, A., & Surendran, S. (2017). Relational to NoSQL database migration. International Journal of Innovative Research in Science, Engineering and Technology, 6(5), 58-62.
[2]. Gharanai, M. H., Gh, R. S., & Ahmadi, A. R. (2016, December). In the digital future: Revitalizing information management systems in Afghan settings through not only SQL (MongoDB) technology. In 2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA) (pp. 45-48). IEEE.
[3]. Hanine, M., Bendarag, A., & Boutkhoum, O. (2016). Data migration methodology from relational to NoSQL databases. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 9(12), 2369-2373.
[4]. Inglés, R., Perek, P., Orlikowski, M., & Napieralski, A. (2015, June). A simple multithreaded C++ framework for high-performance data acquisition systems. In 2015 22nd International Conference Mixed Design of Integrated Circuits & Systems (MIXDES) (pp. 153-157). IEEE.
[5]. Lee, C. H., & Zheng, Y. L. (2015, June). Automatic SQLto- NoSQL schema transformation over the MySQL and HBase databases. In 2015 IEEE International Conference on Consumer Electronics-Taiwan (pp. 426-427). IEEE.
[6]. Liu, J., Du, X., Li, H., & Yang, J. (2017, December). Heterogeneous Learning Resources Integration and Cross- Database Retrieval. In 2017 International Conference of Educational Innovation through Technology (EITT) (pp. 345- 346). IEEE.
[7]. Rocha, L., Vale, F., Cirilo, E., Barbosa, D., & Mourão, F. (2015). A framework for migrating relational datasets to NoSQL. Procedia Computer Science, 51, 2593-2602.
[8]. Symeonaki, E., Papoutsidakis, M., Tseles, D., & Sigala, M. (2016, August). Post-implementation evaluation of a university Management Information System (UMIS). In 2016 Third International Conference on Mathematics and Computers in Sciences and in Industry (MCSI) (pp. 14-19). IEEE.
[9]. Veen, J. S. V. D., Waaij, B. V. D., & Meijer, R. J. (2012, June). Sensor data storage performance: SQL or NoSQL, physical or virtual. In 2012 IEEE Fifth International Conference on Cloud Computing (pp. 431-438). IEEE.
[10]. Zhao, G., Lin, Q., Li, L., & Li, Z. (2014, November). Schema conversion model of SQL database to NoSQL. In 2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (pp. 355-362). IEEE.
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