Big Data Architecture Framework for Data Analysis and Processing in Ecosystem

Chanthirasekaran, K. and Yogeeswaran, S. and Jackulin, T. and Manikanthan, S. V. (2023) Big Data Architecture Framework for Data Analysis and Processing in Ecosystem. International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 12 (2). pp. 435-443. ISSN 2147-6799

[img] Text
J16884_4087ed65d106a06f862584006d1e6318.pdf
Restricted to Registered users only

Download (213kB) | Request a copy

Abstract

Big Data is a well-known buzzword in industry and academics, but there is still much conceptual uncertainty surrounding it, making it difficult to understand what it really means. The phrase is used to denote a wide range of concepts, from technology's ability to receive, repair, and use information to the cultural transformation that is extensively influencing both industries and societies, both of which are drowning in information. Research has gone in a lot of different areas because there is no official definition. This article explores the nature of big data, which can come from various fields of science, business, and social activity. It also suggests an improved big data definition that contains the following elements: Aspects of large data include facilities, safety, data infrastructure, data concepts, and data architectures. This article talks about the paradigm change in big data operations from traditional host- or service-oriented design to data-centric architecture. The Big Data Architecture Framework (BDAF), which is proposed to handle every area of the Big Data Ecosystem, is made up of the following components. As a result, the analysis of big data is currently the subject of study and development. Examining the possible effects of big data challenges, unanswered research problems, and related tools is the primary objective of this work. Thus, this paper provides a paradigm for investigating big data at different stages. Academics now have novel possibilities to develop the solution as a result of the difficulties and open research problems.

Item Type: Article
Uncontrolled Keywords: Unstructured data, Big Data Architecture Framework (BDAF), Ecosystem, bid data technology.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Civil Engineering and Built Environment > FKAAB
Depositing User: Mr. Mohamad Zulkhibri Rahmad
Date Deposited: 27 Nov 2024 03:49
Last Modified: 27 Nov 2024 03:52
URI: http://eprints.uthm.edu.my/id/eprint/11715

Actions (login required)

View Item View Item