Breaking the Silos: Architecting a Real-Time Data Lakehouse for a 100-Node 3PL Network
Legacy 3PLs managing 90+ distribution centers often operate on a patchwork of incompatible WMS, TMS, ERP, and CRM systems. This architecture brief explores how …
Arc Data Insights
In-depth examinations of how modern data engineering, machine learning, and AI can solve the most consequential operational and financial challenges in logistics and 3PL. Framed as solution architecture analysis—not case study marketing.
9 articles in Data Infrastructure
Legacy 3PLs managing 90+ distribution centers often operate on a patchwork of incompatible WMS, TMS, ERP, and CRM systems. This architecture brief explores how …
Most 3PLs use their warehouse management system for basic operational reporting and nothing more. The pick timestamps, exception logs, and inventory snapshots a…
A modern ERP implementation gives finance teams clean, structured financial data. What it does not give them is a connection to operational reality. Bridging th…
Most 3PLs run on nightly batch ETL. Streaming architectures built on Kafka and Flink unlock capabilities that batch processing can never provide: real-time visi…
Every data silo in a logistics organization is a margin tax. Duplicate data entry, reconciliation errors, delayed reporting, and missed optimization opportuniti…
ERP implementation failures in logistics environments are more common and more costly than the vendor case studies suggest. Data gaps, reconciliation nightmares…
The integration between transportation and warehouse management systems is one of the highest-value, most commonly botched data problems in logistics. API-first…
Garbage in, garbage out — the oldest maxim in computing is the most expensive lesson in logistics. Duplicate records, missing timestamps, inconsistent carrier n…
The promise of IoT in logistics — connected dock doors, real-time yard visibility, in-transit sensor monitoring — collides with a fundamental architectural prob…
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