Handling big data: research challenges and future directions

Today, an enormous amount of data is being continuously generated in all walks of life by all kinds of devices and systems every day. A significant portion of such data is being captured, stored, aggregated and analyzed in a systematic way without losing its “4V” (i.e., volume, velocity, variety, an...

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Bibliographic Details
Published in:The Journal of supercomputing 2016-04, Vol.72 (4), p.1494-1516
Main Authors: Anagnostopoulos, I., Zeadally, S., Exposito, E.
Format: Article
Language:English
Subjects:
Compilers
Computer Science
Interpreters
Processor Architectures
Programming Languages
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Summary:Today, an enormous amount of data is being continuously generated in all walks of life by all kinds of devices and systems every day. A significant portion of such data is being captured, stored, aggregated and analyzed in a systematic way without losing its “4V” (i.e., volume, velocity, variety, and veracity) characteristics. We review major drivers of big data today as well the recent trends and established platforms that offer valuable perspectives on the information stored in large and heterogeneous data sets. Then, we present a classification of some of the most important challenges when handling big data. Based on this classification, we recommend solutions that could address the identified challenges, and in addition we highlight cross-disciplinary research directions that need further investigation in the future.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-016-1677-z