Hadoop as Big Data Operating System -- The Emerging Approach for Managing Challenges of Enterprise Big Data Platform

Mazumdar, Sourav; Dhar, Subhankar

doi:10.1109/bigdataservice.2015.72

Cited by 10 publications

(4 citation statements)

References 9 publications

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“…There are tools that have commercial and open-source licensing, and for this work the Apache Hadoop framework is used. Hadoop is an open source tool, widely used by large corporations and has a large amount of information, which makes it easier for technicians to implement it [28]. In Figure 1, the general architecture that facilitates the analysis of the different data sources that are part of the university is presented.…”

Section: Data Analysis Architecturementioning

confidence: 99%

Academic Activities Recommendation System for Sustainable Education in the Age of COVID-19

2021

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Currently, universities are going through a critical moment due to the coronavirus disease in 2019. To prevent its spread, countries have declared quarantines and isolation in all sectors of society. This has caused many problems in the learning of students, since, when moving from a face-to-face educational model to a remote model, several academic factors such as psychological, financial, and methodological have been overlooked. To exactly identify the variables and causes that affect learning, in this work a data analysis model using a Hadoop framework is proposed. By processing the data, it is possible to identify and classify students to determine the problems they present in different learning activities. The results are used by an artificial intelligence system that takes student information and converts it into knowledge, evaluates the academic performance problems they present, and determines what type of activity aligns with the students. The artificial intelligence system processes the information and recommends activities that focus on each student’s abilities and needs. The integration of these systems to universities creates an adaptive educational model that responds to the new challenges of society.

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Section: Data Analysis Architecturementioning

confidence: 99%

Academic Activities Recommendation System for Sustainable Education in the Age of COVID-19

2021

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“…The scalability of Hadoop allows the analysis to be carried out with the data of the students in a face-to-face education model and contrast it with the data of the new modality by which the students are studying. In this way, it is possible to obtain a guide based on the results of the data analysis to generate a hybrid education modality that guarantees learning [41].…”

Section: Data Analysis Modelmentioning

confidence: 99%

Analysis of Educational Data in the Current State of University Learning for the Transition to a Hybrid Education Model

et al. 2021

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Currently, the 2019 Coronavirus Disease pandemic has caused serious damage to health throughout the world. Its contagious capacity has forced the governments of the world to decree isolation and quarantine to try to control the pandemic. The consequences that it leaves in all sectors of society have been disastrous. However, technological advances have allowed people to continue their different activities to some extent while maintaining isolation. Universities have great penetration in the use of technology, but they have also been severely affected. To give continuity to education, universities have been forced to move to an educational model based on synchronous encounters, but they have maintained the methodology of a face-to-face educational model, what has caused several problems in the learning of students. This work proposes the transition to a hybrid educational model, provided that this transition is supported by data analysis to identify the new needs of students. The knowledge obtained is contrasted with the performance presented by the students in the face-to-face modality and the necessary parameters for the transition to this modality are clearly established. In addition, the guidelines and methodology of online education are considered in order to take advantage of the best of both modalities and guarantee learning.

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“…If there is a variable that does not correspond or the inclusion of data from other sources is necessary, the process returns to the stage of "Process of the request", where they are loaded again the data corresponding to the validation carried out. On the contrary, if the validation is correct, the process continues the flow to the next level where it prepares the results by means of different tools established in the big data model [55].…”

Section: Integration Of a Big Data Model In Adaptive Learningmentioning

confidence: 99%

Data Analysis as a Tool for the Application of Adaptive Learning in a University Environment

et al. 2020

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Currently, data are a very valuable resource for organizations. Through analysis, it is possible to profile people or obtain knowledge about an event or environment and make decisions that help improve their quality of life. This concept takes on greater value in the current pandemic, due to coronavirus disease 2019 (COVID-19), that affects society. This emergency has changed the way people live. As a result, the majority of activities are carried out using the internet, virtually or online. Education is not far behind and has seen the web as the most successful option to continue with its activities. The use of any computer application generates a large volume of data that can be analyzed by a big data architecture in order to obtain knowledge from its students and use it to improve educational processes. The big data, when included as a tool for adaptive learning, allow the analysis of a large volume of data to offer an educational model based on personalized education. In this work, the analysis of educational data through a big data architecture is proposed to generate learning based on meeting the needs of students.

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Hadoop as Big Data Operating System -- The Emerging Approach for Managing Challenges of Enterprise Big Data Platform

Cited by 10 publications

References 9 publications

Academic Activities Recommendation System for Sustainable Education in the Age of COVID-19

Academic Activities Recommendation System for Sustainable Education in the Age of COVID-19

Analysis of Educational Data in the Current State of University Learning for the Transition to a Hybrid Education Model

Data Analysis as a Tool for the Application of Adaptive Learning in a University Environment

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