The Role of Cloud-Based Analytics in Transforming Logistics Data Management and Reporting

Cloud-based analytics has transformed logistics data management by enabling real-time data processing, improving visibility, and supporting fact-based decision-making. Traditional logistics systems struggle with data silos, delayed reporting, and poor resource planning. Cloud-based solutions dynamically process vast logistics data, allowing real-time monitoring of transportation, inventory, and supplier performance. This improves efficiency by identifying bottlenecks, streamlining routes, and predicting disruptions. AI-powered analytics also enables demand forecasting, warehouse optimization, and automated strategic decisions. Moreover, cloud-based platforms integrate data from suppliers, distributors, and logistics providers, enhancing collaboration, reducing communication gaps, and improving regulatory compliance. Security and scalability further drive adoption, with cloud providers offering encryption, access controls, and real-time threat detection. Flexible cloud infrastructure allows businesses to scale analytics based on demand, cutting infrastructure costs while maintaining high performance. In summary, cloud-based analytics offers real-time insights, predictive capabilities, collaboration, and secure scalability, helping firms improve efficiency, reduce risks, and stay competitive in global supply chains.

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Publication Details

Journal
The Eastasouth Journal of Information System and Computer Science
Published
2024-12-31
DOI
https://doi.org/10.58812/esiscs.v2i02.515
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
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article

The Role of Cloud-Based Analytics in Transforming Logistics Data Management and Reporting

Srikanth Yerra
1 citations
The Eastasouth Journal of Information System and Computer Science
Big Data and Business Intelligence
0.53
article

The Role of Cloud-Based Analytics in Transforming Logistics Data Management and Reporting

Srikanth Yerra
article en
1 citations

Abstract

Cloud-based analytics has transformed logistics data management by enabling real-time data processing, improving visibility, and supporting fact-based decision-making. Traditional logistics systems struggle with data silos, delayed reporting, and poor resource planning. Cloud-based solutions dynamically process vast logistics data, allowing real-time monitoring of transportation, inventory, and supplier performance. This improves efficiency by identifying bottlenecks, streamlining routes, and predicting disruptions. AI-powered analytics also enables demand forecasting, warehouse optimization, and automated strategic decisions. Moreover, cloud-based platforms integrate data from suppliers, distributors, and logistics providers, enhancing collaboration, reducing communication gaps, and improving regulatory compliance. Security and scalability further drive adoption, with cloud providers offering encryption, access controls, and real-time threat detection. Flexible cloud infrastructure allows businesses to scale analytics based on demand, cutting infrastructure costs while maintaining high performance. In summary, cloud-based analytics offers real-time insights, predictive capabilities, collaboration, and secure scalability, helping firms improve efficiency, reduce risks, and stay competitive in global supply chains.

The Eastasouth Journal of Information System and Computer ScienceVol. 2(02)
University of Memphis (US)
Openalex Percentile: Top 21%
Big Data and Business Intelligence
0.53
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