Real-Time Analytics with Event-Driven Architectures: Powering Next-Gen Business Intelligence

Dr. Erik, Svensson and Emma, Larsson (2018) Real-Time Analytics with Event-Driven Architectures: Powering Next-Gen Business Intelligence. International Journal of Trend in Scientific Research and Development, 2 (4). pp. 3097-3111. ISSN 2456-6470

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Abstract

In today’s fast-paced business environment, organizations are increasingly leveraging real-time analytics to drive timely, data-informed decision-making. Event-driven architectures (EDAs) have emerged as a critical enabler of next-generation business intelligence (BI), offering businesses the ability to respond dynamically to real-time data streams and events as they unfold. This article explores the transformative potential of real-time analytics within event-driven architectures, highlighting their ability to process large volumes of data instantaneously and provide insights at the point of action. Unlike traditional BI systems that rely on batch processing and periodic data aggregation, event-driven architectures offer continuous, real-time data processing, enabling businesses to monitor, analyze, and respond to events across various touchpoints in real time. Through an exploration of key concepts such as data streams, event processing, and microservices, this article outlines how real-time analytics integrated with event-driven systems allows businesses to unlock operational agility, enhance customer experiences, and drive predictive insights. Furthermore, the article delves into the practical applications of these technologies in industries such as e-commerce, healthcare, and finance, where real-time decision-making is critical. The piece concludes by discussing the challenges and opportunities in adopting event-driven architectures, including data consistency, scalability, and the integration of legacy systems, while emphasizing how organizations can future-proof their BI strategies with event-driven approaches. Ultimately, the convergence of real-time analytics and event-driven architectures marks a paradigm shift in how businesses leverage data for continuous innovation and competitive advantage.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	22 Nov 2024 11:07
Last Modified:	22 Nov 2024 11:07
URI:	http://eprints.umsida.ac.id/id/eprint/14668

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