DHL — RMA LOGISTICS
Hybrid Azure Databricks data platform with AI-powered process automation for DHL in partnership with RMA Logistics.
2025
Hybrid Data & AI Platform
Active
RMA Logistics, a regional hub for DHL, needed to bridge fragmented on-premise data systems with cloud infrastructure. NexOps designed and implemented a hybrid Azure Databricks environment that centralised scattered data sources — Excel files, local databases, and siloed departmental systems — and automated manual data-intensive processes using AI and machine learning, enabling real-time data processing, predictive analytics, and intelligent decision-making across the organisation.
METHODOLOGY
- 01
Architected a hybrid Azure Databricks solution with VPN tunnels, ExpressRoute, and private endpoints for secure on-premise to cloud connectivity
- 02
Built a unified Databricks Lakehouse eliminating scattered Excel files, local databases, and siloed data sources, connecting multiple regional distribution centres
- 03
Automated invoice processing workflows using AI-powered document extraction and classification, financial reconciliation, and daily/weekly/monthly operational reporting — replacing manual Excel-based processes
- 04
Implemented AI-driven anomaly detection on Databricks, real-time performance dashboards, and self-service analytics enabling business users to access data independently
- 05
Deployed Databricks ML models for demand forecasting and shipment volume prediction across distribution centres
- 06
Established Azure DevOps CI/CD pipelines and Terraform IaC for automated deployment and hybrid infrastructure management
OUTCOMES
- →
99.5% time reduction — invoice processing reduced from 2 days of manual work to under 10 seconds
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Eliminated data silos — unified fragmented sources into a Databricks Lakehouse as single source of truth across the organisation
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AI-driven demand forecasting enabling proactive resource allocation across distribution centres
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Enabled real-time operational insights previously requiring days of manual data compilation
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Reduced operational costs through AI automation and elimination of manual data processing
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