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Open Access Journal Article

Real-Time Analytics for Operational Efficiency

by Daniel Thomas 1,*
1
Daniel Thomas
*
Author to whom correspondence should be addressed.
MAD  2022 4(2):35; https://doi.org/10.69610/j.mad.20221130
Received: 22 September 2022 / Accepted: 21 October 2021 / Published Online: 30 November 2022
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Abstract

The title "Real-Time Analytics for Operational Efficiency" reflects the growing importance of leveraging real-time analytics to enhance business operations. This paper explores the integration of real-time analytics into various operational processes, aiming to improve efficiency, productivity, and decision-making. Real-time analytics involves the use of advanced data processing techniques to analyze and interpret data as it is generated, providing organizations with instant insights and actionable information. The study delves into the benefits of real-time analytics, including reduced response times, better resource allocation, and increased customer satisfaction. Additionally, the paper examines the challenges associated with implementing real-time analytics, such as data quality, technology requirements, and talent acquisition. Through case studies and industry examples, this research highlights the practical applications of real-time analytics across different sectors, demonstrating its potential to transform operational practices and drive sustainable growth.

Keywords: Real-Time Analytics; Operational Efficiency; Business Operations; Data Processing; Decision-Making.;
Copyright: © 2022 by Thomas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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APA Style
Thomas, D. (2022). Real-Time Analytics for Operational Efficiency. Management Analytics and Decision, 4(2), 35. doi:10.69610/j.mad.20221130
ACS Style
Thomas, D. Real-Time Analytics for Operational Efficiency. Management Analytics and Decision, 2022, 4, 35. doi:10.69610/j.mad.20221130
AMA Style
Thomas D. Real-Time Analytics for Operational Efficiency. Management Analytics and Decision; 2022, 4(2):35. doi:10.69610/j.mad.20221130
Chicago/Turabian Style
Thomas, Daniel 2022. "Real-Time Analytics for Operational Efficiency" Management Analytics and Decision 4, no.2:35. doi:10.69610/j.mad.20221130

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ACS Style
Thomas, D. Real-Time Analytics for Operational Efficiency. Management Analytics and Decision, 2022, 4, 35. doi:10.69610/j.mad.20221130
AMA Style
Thomas D. Real-Time Analytics for Operational Efficiency. Management Analytics and Decision; 2022, 4(2):35. doi:10.69610/j.mad.20221130
Chicago/Turabian Style
Thomas, Daniel 2022. "Real-Time Analytics for Operational Efficiency" Management Analytics and Decision 4, no.2:35. doi:10.69610/j.mad.20221130
APA style
Thomas, D. (2022). Real-Time Analytics for Operational Efficiency. Management Analytics and Decision, 4(2), 35. doi:10.69610/j.mad.20221130

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