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Paper details
Number 4 - December 2017
Volume 27 - 2017
Exploring complex and big data
Jerzy Stefanowski, Krzysztof Krawiec, Robert Wrembel
Abstract
This paper shows how big data analysis opens a range of research and technological problems and calls for new approaches.
We start with defining the essential properties of big data and discussing the main types of data involved. We then survey
the dedicated solutions for storing and processing big data, including a data lake, virtual integration, and a polystore architecture. Difficulties in managing data quality and provenance are also highlighted. The characteristics of big data
imply also specific requirements and challenges for data mining algorithms, which we address as well. The links with
related areas, including data streams and deep learning, are discussed. The common theme that naturally emerges from
this characterization is complexity. All in all, we consider it to be the truly defining feature of big data (posing particular
research and technological challenges), which ultimately seems to be of greater importance than the sheer data volume.
Keywords
big data, complex data, data integration, data provenance, data streams, deep learning