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Logistics and Supply Chain Performance Dashboard

Smruti Ranjan Swain Smruti Ranjan Swain,Priyanka Behera Priyanka Behera

2026 · DOI: 10.55041/ijsmt.v2i6.064
0 Citations

TLDR

The developed dashboard helps organizations identify operational bottlenecks, improve supply chain visibility, and support strategic decision-making and demonstrates how modern big data technologies, Medallion Architecture, and dashboard visualization tools can be effectively utilized for intelligent logistics analytics and supply chain performance management.

Abstract

The rapid growth of global trade, e-commerce, and transportation systems has significantly increased the complexity of logistics and supply chain operations. Organizations generate large volumes of logistics data from shipment records, inventory updates, supplier information, transportation costs, and delivery activities. Efficient analysis of this data is essential for improving operational visibility, reducing delays, optimizing inventory management, and supporting data-driven business decisions. This paper presents a Logistics and Supply Chain Performance Dashboard developed using the Databricks Lakehouse Platform and Medallion Architecture for scalable logistics data processing and analytical reporting.

The proposed system processes logistics datasets through Bronze, Silver, and Gold layers to improve data quality, perform transformation, and generate meaningful business insights. Interactive dashboards and visualization techniques are used to monitor key performance indicators (KPIs) such as delivery performance, transportation costs, supplier efficiency, inventory levels, and order fulfillment status through charts, KPI cards, and analytical reports. The developed dashboard helps organizations identify operational bottlenecks, improve supply chain visibility, and support strategic decision-making. This research demonstrates how modern big data technologies, Medallion Architecture, and dashboard visualization tools can be effectively utilized for intelligent logistics analytics and supply chain performance management.