工业大数据

T. Latinovic, D. Preradovic, C. Barz, M. Latinovic, P. Petrica, A. Pop-Vǎdean
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引用次数: 8

摘要

全球数据量呈指数级增长。伴随着这种现象,我们需要一种新的度量单位,如exabyte、zettabyte和yottabyte,作为最后一个度量数据量的单位。数据的增长导致了这样一种情况:用于数据收集、存储、处理和可视化的经典系统在不断生成的大量、快速和各种数据的竞争中败下阵来。许多数据是由物联网(IoT)(摄像头、卫星、汽车、GPS导航等)创建的。我们面临的挑战是找到新的技术和工具来管理和利用这些大量的数据。大数据是近年来IT界的一个热门话题。然而,大数据在商业领域得到了认可,并越来越多地在公共管理领域得到认可。本文提出了大数据分析的本体,并通过提出大数据分析面向服务的体系结构,探讨了如何通过大数据分析作为服务来增强商业智能。本文还讨论了商业智能和大数据分析之间的相互关系。本文提出的方法可以促进商业分析、大数据分析、商业智能以及智能代理的研究和发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data in industry
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.
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