Authors: T S Latinović, D M Preradović, C R Barz, M T Latinović, P P Petrica and A Pop-Vadean


Journal: IOP Conference Series: Materials Science and Engineering


Publisher: IOP Publishing Ltd
The amount of data at the global level has grown exponentially. Along with this phenomena, we have a need for a new unit of measure like exabyte, zettabyte, and yottabyte as the last unit measures the amount of data. The growth of data gives a situation where the classic systems for the collection, storage, processing, and visualization of data losing the battle with a large amount, speed, and variety of data that is generated continuously. Many of data that is created by the Internet of Things, IoT (cameras, satellites, cars, GPS navigation, etc.). It is our challenge to come up with new technologies and tools for the management and exploitation of these large amounts of data. Big Data is a hot topic in recent years in IT circles. However, Big Data is recognized in the business world, and increasingly in the public administration.
This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence

Illustration Photo: Airbus A380 Flight test station (credits: Todd Lappin / Flickr Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

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