Big data challenges in information engineering curriculum
Loading...

Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE Computer Society help@computer.org
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
The amount of accumulated data is growing at unprecedented rates. This data is mainly unstructured or semi structured and comes from different sources in a variety of forms. Recently a range of supporting storage and distributed parallel computing technologies have been developed and put into use by the sector.The products and implementations include, Apache's Hadoop data processing framework Map Reduce distributed big data management system Cassandra and other NoSQL database and data storage systems. Among the major challenges are, data representation reliable shared storage efficient algorithms and scalable distributed HW/SW infrastructures. Surprisingly current curricula lack the necessary components to create awareness and a good understanding of these state of the art concepts and technologies. There is an urgent need for integrating the developments in big data technologies into the educational programs and computing curricula. This need not only is dictated by the industry but also by the employement dynamics in the related professions. This paper discusses fundemental big data issues and technologies that are considered to be necessary for the existing educational programs in computing information systems and information engineering areas. © 2014 IEEE. © 2014 Elsevier B.V. All rights reserved.
Description
ORCID
Keywords
Big Data, Hadoop Hdfs, Nosql, Unstructured Data, Algorithms, Curricula, Digital Storage, Distributed Database Systems, Engineering Education, Information Management, Parallel Architectures, Data Management System, Data Storage Systems, Distributed Parallel Computing, Hadoop Hdfs, Information Engineerings, Nosql, Systems And Information, Unstructured Data, Big Data, Algorithms, Curricula, Digital storage, Distributed database systems, Engineering education, Information management, Parallel architectures, Data management system, Data storage systems, Distributed parallel computing, Hadoop HDFS, Information engineerings, NoSQL, Systems and information, Unstructured data, Big data, Unstructured Data, Big Data, Hadoop HDFS, Nosql
Fields of Science
0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
4
Source
25th International Conference on European Association for Education in Electrical and Information Engineering EAEEIE 2014
Volume
Issue
Start Page
1
End Page
4
PlumX Metrics
Citations
CrossRef : 2
Scopus : 9
Captures
Mendeley Readers : 28
SCOPUS™ Citations
9
checked on Apr 09, 2026
Web of Science™ Citations
4
checked on Apr 09, 2026
Google Scholar™


