A Parallel Platform for Big Data Analytics: A Design Science Approach

International Journal of Computer Science Engineering and Technology (IJCSET). Volume 3, Issue 5, 152-156, 2013

Posted: 2 Aug 2013

See all articles by Claudia Loebbecke

Claudia Loebbecke

University of Cologne - Department of Media and Technology Management

Joerg Bienert

ParStream GmbH

Ali Sunyaev

University of Cologne

Date Written: 2013

Abstract

Following a Design Science approach, at the core of this paper we propose a technically innovative parallel platform for Big Data analytics. The design of the proposed platform allows for analyzing and filtering billions of records, querying data structures with 1,000s of columns, getting answers in milliseconds without cubes, continuously importing data with low latency, and executing 1,000s of concurrent queries. Deploying the platform has empowered organizations across many industries to capture new business opportunities from better analytic quality of very large, close to real-time data. With our single platform design project, we hope to provide an interim attempt at theorizing about achieving data quality and business opportunities from Big Data analytics.

Keywords: Big Data Analytics, Parallel Platform Design, Design Science

Suggested Citation

Loebbecke, Claudia and Bienert, Joerg and Sunyaev, Ali, A Parallel Platform for Big Data Analytics: A Design Science Approach (2013). International Journal of Computer Science Engineering and Technology (IJCSET). Volume 3, Issue 5, 152-156, 2013. Available at SSRN: https://ssrn.com/abstract=2304813

Claudia Loebbecke

University of Cologne - Department of Media and Technology Management ( email )

Pohligstr. 1
Cologne, 50969
Germany

Joerg Bienert

ParStream GmbH ( email )

Grosse Sandkaul 2
Cologne, 50667
Germany

Ali Sunyaev (Contact Author)

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

HOME PAGE: http://www.isq.uni-koeln.de

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