Towards an Integrated Platform for Big Data Analysis

TL;DR

This paper proposes an integrated platform for big data analysis that combines data management, processing, and visualization to improve scalability, resource efficiency, and usability in handling massive datasets.

Contribution

It introduces a comprehensive platform that unifies various aspects of big data analysis, addressing limitations of existing approaches that focus on only one or two aspects.

Findings

Enhanced scalability of the analysis platform

Improved parameterization of algorithms

More efficient system resource utilization

Abstract

The amount of data in the world is expanding rapidly. Every day, huge amounts of data are created by scientific experiments, companies, and end users' activities. These large data sets have been labeled as "Big Data", and their storage, processing and analysis presents a plethora of new challenges to computer science researchers and IT professionals. In addition to efficient data management, additional complexity arises from dealing with semi-structured or unstructured data, and from time critical processing requirements. In order to understand these massive amounts of data, advanced visualization and data exploration techniques are required. Innovative approaches to these challenges have been developed during recent years, and continue to be a hot topic for re-search and industry in the future. An investigation of current approaches reveals that usually only one or two aspects are ad-dressed, either in the data management, processing, analysis or visualization. This paper presents the vision of an integrated plat-form for big data analysis that combines all these aspects. Main benefits of this approach are an enhanced scalability of the whole platform, a better parameterization of algorithms, a more efficient usage of system resources, and an improved usability during the end-to-end data analysis process.