Title :
Big Data Framework
Author :
Tekiner, Firat ; Keane, John A.
Author_Institution :
Sch. of Comput. Sci., Univ. of Manchester, Manchester, UK
Abstract :
We are constantly being told that we live in the Information Era - the Age of BIG data. It is clearly apparent that organizations need to employ data-driven decision making to gain competitive advantage. Processing, integrating and interacting with more data should make it better data, providing both more panoramic and more granular views to aid strategic decision making. This is made possible via Big Data exploiting affordable and usable Computational and Storage Resources. Many offerings are based on the Map-Reduce and Hadoop paradigms and most focus solely on the analytical side. Nonetheless, in many respects it remains unclear what Big Data actually is, current offerings appear as isolated silos that are difficult to integrate and/or make it difficult to better utilize existing data and systems. Paper addresses this lacunae by characterising the facets of Big Data and proposing a framework in which Big Data applications can be developed. The framework consists of three Stages and seven Layers to divide Big Data application into modular blocks. The aim is to enable organizations to better manage and architect a very large Big Data application to gain competitive advantage by allowing management to have a better handle on data processing.
Keywords :
Big Data; SQL; competitive intelligence; data integration; Big Data application division; Big Data framework; computational resources; data integration; data interaction; data processing; data-driven decision making; modular blocks; organizational aspects; storage resources; strategic decision making; Data handling; Data models; Data storage systems; Decision making; Information management; Organizations; Big Data; analytics; business intelligence; data scientist; hadoop; information management; strategy;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
DOI :
10.1109/SMC.2013.258