Around the world, freight organisations are moving away from single-point transport management to a multi-entity, multi-node, cross-system collaborative model. Freight visualisation platforms need to offer continuous status information on all parts of an order, such as orders, vehicles, cargo, ports, warehouses, customs and customer service. To address the problems of delayed data arrival, inconsistencies in status descriptions, insufficient anomaly alerts, and high system expansion costs, a data-distributed pipeline and event-driven architecture model suitable for multimodal transport scenarios have been established. Event domains in the freight lifecycle include order creation, loading, in transit, arrival, transshipment, receipt and anomaly closure. The design will focus on event themes, streaming cleansing, state machine aggregation, idempotent writing and observable governance. Prototype load test logs are used to verify the end-to-end latency, visualisation gaps, event consistency and anomaly response capabilities. Based on the above analysis, after implementing a Kafka-Flink-style event pipeline, the P95 event latency dropped from 9.42s in the polling integration mode to 1.31s, the gap in abnormal event visualisation reduced from 58.6% to over 41.4%, and the state consistency still exceeded 99.30%. This study offers a reproducible architectural blueprint and engineering evaluation indicators for third-party logistics, port collaboration, cross-border transportation platforms and supply chain control tower construction.

Haoran Xin. Research on Distributed Data Pipelines and Event-Driven Architecture for Freight Visibility. International Journal of Business Management and Economics and Trade (2026), Vol. 7, Issue 3: 10-22. https://doi.org/10.38007/IJBMET.2026.070302.

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