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Building a Big Data Oriented Architecture for Enterprise Integration

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Cooperative Design, Visualization, and Engineering (CDVE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12983))

Abstract

Digital transformation is happening across all industries and affecting all facets of our daily life. However, in many corporations, this important process is fragmented and is undertaken without a farsighted plan to take advantage of an invaluable resource: data. This can be due to a variety of reasons, for example, lack of funding, poor business vision, inappropriate consulting or deployment. Digital transformation is a considerable investment since it will determine the system’s ability to grow and adapt to the company’s changing requirements. To achieve that end, the architecture must be flexible both in development and deployment and must also be able to harness the ever-increasing data of the corporation. Among the widely used information system architectures being used in the world, Micro-service is a standout with many advantages. The adaptation of this architecture to work with Big Data, as well as to tackle different aspects of a data system such as load-balancing, file handling and storage, etc. is a very practical area of research. This paper presents such an enterprise integration solution for a mega-corporation client in Vietnam, the An Pha Petrol Group Joint Stock Company, including the architecture and technologies used to build a comprehensive system that brings novel experiences to its 2,000 internal users. It consists of building the information infrastructure and system, super applications for both desktop and mobile devices to enhance the work performance and quality. The approaches and results of this paper are applicable to similar large enterprise solutions.

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Correspondence to Phan Duy Hung .

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Nam, L.H., Hung, P.D. (2021). Building a Big Data Oriented Architecture for Enterprise Integration. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2021. Lecture Notes in Computer Science(), vol 12983. Springer, Cham. https://doi.org/10.1007/978-3-030-88207-5_17

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  • DOI: https://doi.org/10.1007/978-3-030-88207-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88206-8

  • Online ISBN: 978-3-030-88207-5

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