use case

Data operation optimization – Transportation & Logistics

The challenge

Supply chain operations were fragmented across multiple ERPs, logistics, and supplier systems. Data silos led to delays in visibility, limited forecasting capabilities, and challenges in managing supplier performance and inventory planning.

Our solution

Building a centralized supply chain data lake and developing scalable pipelines to ingest and harmonize live shipment updates, purchase orders, warehouse stock data, and supplier performance metrics. The solution integrated predictive analytics for inventory optimization and supplier risk assessment, alongside real-time dashboards for procurement and operations teams.

Business impact

Real-time supply chain visibility across procurement, logistics, and supplier performance
Forecasting accuracy improved for inventory levels and delivery times
Optimized lead times and reduction in stock-outs
Strengthened supplier risk assessment and faster, data-driven decision-making
Streamlined, automated processes replacing manual reporting

Result

Reduced stock-outs by up to 20% through predictive analytics
Improved operational efficiency by eliminating fragmented data handling
Faster procurement decisions with drill-down insights in BI dashboards
Improved collaboration with external partners via secure, simplified data sharing

Technology Stack & Expertise

Data Processing: Databricks (Notebooks, Jobs, Autoloader), Azure Batch, Airflow
Data Warehousing: Snowflake (Gold Layer), dbt (semantic modeling & transformations)
Architecture: Medallion (Bronze → Silver → Gold), ensuring traceability, scalability, and quality
Analytics & Visualization: Power BI dashboards with Row-Level Security (RLS), Sigma, and custom AI apps
Integrations: APIs (Atlassian, Chargebee, Amplitude, GA4), Excel ingestion