Exploring Oracle APEX for the University Data Analysis

This paper delves into Oracle Application Express (APEX), a robust platform for web application development, showcasing its merits and suitability for creating a comprehensive Analytical Tool for University Data Management application. This application serves as an integrated solution to analyse var...

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Vydáno v:2023 21st International Conference on Emerging eLearning Technologies and Applications (ICETA) s. 395 - 402
Hlavní autoři: Pastierik, Ivan, Kvet, Michal
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 26.10.2023
Témata:
Aerodynamics
Data analysis
Machine learning
Manuals
Scalability
Visualization
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Shrnutí:This paper delves into Oracle Application Express (APEX), a robust platform for web application development, showcasing its merits and suitability for creating a comprehensive Analytical Tool for University Data Management application. This application serves as an integrated solution to analyse various facets of university processes, such as student interactions, faculty engagement, study group dynamics, and subject performance, utilizing visual representations like graphs and charts. Beyond data analysis, the application also works as an Academic Information System, proficiently storing and managing student-centric information, including exam results and enrolled subjects. The initial sections of the paper explore the features and capabilities of Oracle APEX, highlighting its role as a low-code development platform that empowers developers to create sophisticated web applications with efficiency. The focal point of this study is the presentation of the Analytical Tool for University Data Management application created using Oracle APEX. By harnessing various modules and regions within Oracle APEX, the application offers a user-friendly interface that facilitates comprehensive data analysis. The application's ability to present individual and aggregate statistics through graphical visualizations empowers decision-makers with insightful information. The application holds great potential for future expansion utilising Machine Learning methods.
DOI:10.1109/ICETA61311.2023.10344058