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Enhancing Stock Market Analytics in Real Time With Apache Kafka
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Author(s): Lavanya Kandasamy (Vellore Institute of Technology, India), Swarnava Dey (Vellore Institute of Technology, India), Debdyuti Mitra (Vellore Institute of Technology, India)and Dhaivat Jambudia (Vellore Institute of Technology, India)
Copyright: 2026
Pages: 20
Source title:
AI-Driven Decision-Making for Diversity, Equity, and Inclusion in Marketing
Source Author(s)/Editor(s): Theodore Tarnanidis (International Hellenic University, Greece)
DOI: 10.4018/979-8-3373-6731-6.ch008
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Abstract
Modern structure of financial system relies strongly on live trend of stock-market price and the real-time deviations of values that enriches a healthy competition and instant decision-making capability in a fast-moving market environment. Due to the inherent dynamic properties of big data, it becomes challenging for typical data-mining tools, technologies, methods and techniques to be applied on big-data streaming task. The significant resistance faced by real time streaming of big data involves lack of adaptability, controllability and programmability. Apache kafka is one of the best frameworks to work with for resolving real time data streaming tasks for its unique characteristics of being reliable, distributed and having high throughput and low latency. The essential features of kafka are thoroughly summarized in this abstract which empowers market regulators to manage and analyze stock value movement in a real-time manner to cop up with momentary changes.
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