Abstract
In recent years, vast and complex amounts of data are being created and making it difficult for traditional data processing applications to manage them. The coming of the Internet prompted monstrous spike in the volume of information being made and made accessible. World Wide Web consortium W3C and international standardization body of the web spread the Semantic Web. It is an extended form of current web which provide easier way to search, reuse, combine and share information. In the last few years, major businesses corporations have demonstrated interest in incorporating semantic web technology with big data for added value. Indeed this incorporation has some benefits as well; it increases end-users ability to self-manage data from various sources, it on focuses changing business environments and varying user needs and handles concepts and relationships, manages terminology while connecting different data from varied data sources. For Social Network Analysis (SNA) new methods are needed by combining Big Data and Semantic Web technologies as a way to utilize and add capacities to existing frameworks. Moreover, the fast changing business requirements and latest industry culture of Agile Development needs a robust yet flexible solution for Business Intelligence and by using distributed enterprise level ontologies Data Warehousing can be incorporated. This paper is an attempt to focus on effects of incorporating Big Data with Semantic web, how Semantic Web making Big Data smarter, revisit the Big Data and Semantic Web challenges and opportunities, relationship between them and finally we summarizes with future direction of this integration
Highlights
The recent growth of business processes and electronic data management brought a number of improvements for enterprises, such as selling products, automatic handling of purchasing
Data that is inconsistent with each other, unable to reflect the link between the data sets and could not understand each other is referred as Semantic heterogeneous data [11]
In this paper we present a brief survey of the technological aspects related to big data in terms of structured, semi structured and unstructured data from distinct sources and their inconsistencies with related to structural and semantic heterogeneity
Summary
The recent growth of business processes and electronic data management brought a number of improvements for enterprises, such as selling products, automatic handling of purchasing. By the increase of complexity required to handle more and more business processes and electronic data; enterprises are challenged by these complexities. This issue is discussed in context of big data. Many organizations are not ready to implement such an information framework into their information technology structure as procedures for information and business process integration are still too exorbitant and Tedious for them This can results in higher number of inconsistencies and data redundancy within the product information of an enterprise [5].
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