Contributions to Books:
M. Bohlouli, F. Schulz, L. Angelis, D. Pahor, I. Brandic, D. Atlan, R. Tate:
"Towards an Integrated Platform for Big Data Analysis";
in: "Integration of Practice-Oriented Knowledge Technology: Trends and Prospectives",
M. Fathi (ed.);
Springer-Verlag Berlin Heidelberg,
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 research and industry in the future. An investigation of current approaches reveals that usually only one or two aspects are addressed, either in the data management, processing, analysis or visualization.
This paper presents the vision of an integrated platform 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-toend data analysis process.
Scalable Decision Support, Complex Event Processing, Big Data, Cloud Computing.
Created from the Publication Database of the Vienna University of Technology.