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International Journal of Data Mining And Emerging Technologies
Year : 2018, Volume : 8, Issue : 2
First page : ( 150) Last page : ( 156)
Print ISSN : 2249-3212. Online ISSN : 2249-3220.
Article DOI : 10.5958/2249-3220.2018.00017.4

Data Visualisation and Analysis of Engineering Educational Statistics

Urolagin Siddhaling1,*, Upadhyaya Ishita1,**, Thakur Afrah Abbas1,***

Dubai International Academic City, Dubai, UAE

1Department of Computer Science, Birla Institute of Technology & Science, Pilani

*Corresponding author email id: siddhaling@dubai.bits-pilani.ac.in

**ishita.upadhyaya03@gmail.com

***afrah_abbas@hotmail.com

Online published on 7 January, 2019.

Abstract

Engineering is one of the most popular fields of higher education in the modern day world. Majority of the students these days opt for engineering as a career, due to the vastness of choices provided by engineering. Mechanical, electrical, computer science, civil and biotechnology are the various disciplines and have varying strength in terms of the number of students who join a particular discipline. In this research, we have gathered data from various published articles about engineering education and carried out the data visualisation and analysis using Tableau 9.2. The objective of the analysis is to help the students to make the decision and the choice about the discipline of engineering from which particular university would be the most suitable based on the data collected and represented. Various categories of statistics such as the number of graduates from a particular university in a particular discipline, and which university had the maximum number of graduates in a certain year will help the students make their decisions about their future in easier and a sorted manner.

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Keywords

Engineering education, Data visualisation, Statistical analysis, Employment, University education, Salary, Engineering Disciplines.

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