<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The issues related to the analysis and management of Big Data, aspects of the security, stability and quality of the data, represent a new research, and engineering challenge. In the present paper, techniques for Big Data storage, search, analysis and management in the area of the virtual e-Learning space and the problems in front of them are considered. A numerical example for explorative analysis of data about the students from Burgas Free University is applied, using instrument for Data Mining of Orange. The analysis is a base for a system for localization of students at risk.</p></abstract>

The issues related to the analysis and management of Big Data, aspects of the security, stability and quality of the data, represent a new research, and engineering challenge. In the present paper, techniques for Big Data storage, search, analysis and management in the area of the virtual e-Learning space and the problems in front of them are considered. A numerical example for explorative analysis of data about the students from Burgas Free University is applied, using instrument for Data Mining of Orange. The analysis is a base for a system for localization of students at risk.

Towards Big Data Analytics in the e-Learning Space

Institute of Information and Communication Technologies

Faculty of Computer Science and Engineering

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Towards Big Data Analytics in the e-Learning Space"}

The issues related to the analysis and management of Big Data, aspects of the security, stability and quality of the data, represent a new research, and...

Towards Big Data Analytics in the e-Learning Space

Online veröffentlicht: 26. Sept. 2019

Seitenbereich: 16 - 24

Eingereicht: 21. Juni 2019

Akzeptiert: 05. Aug. 2019

DOI: https://doi.org/10.2478/cait-2019-0023

Schlüsselwörter
Big Data Analytics, Data Mining, Map/Reduce, e-Learning, Orange

© 2019 Ivan P. Popchev et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Towards Big Data Analytics in the e-Learning Space

Online veröffentlicht: 26. Sept. 2019

Seitenbereich: 16 - 24

Eingereicht: 21. Juni 2019

Akzeptiert: 05. Aug. 2019

DOI: https://doi.org/10.2478/cait-2019-0023

SchlüsselwörterBig Data Analytics, Data Mining, Map/Reduce, e-Learning, Orange

© 2019 Ivan P. Popchev et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Big Data Analytics, Data Mining, Map/Reduce, e-Learning, Orange