Real-time Supply Chain Solutions with Databricks & Kafka
Embark on an exhilarating journey to construct cutting-edge real-time supply chain intelligence solutions from the ground up. This guide will lead you through designing and deploying robust systems for event ingestion, tariff analysis, cost monitoring, and procurement price intelligence using Databricks, Kafka, and Delta Lake. Get ready to transform raw data into actionable insights, driving efficiency and predictive power across your supply chain operations.
Chapters
- 01 Setting Up Your Databricks Lakehouse Environment 18m
- 02 Simulating Real-time Supply Chain Events with Kafka 20m
- 03 Ingesting Raw Supply Chain Events with DLT Bronze Layer 19m
- 04 Refining Supply Chain Events for Delay Analytics (Silver Layer) 15m
- 05 Real-time Supply Chain Delay Analytics (Gold Layer) 21m
- 06 Ingesting & Harmonizing HS Code and Tariff Data 22m
- 07 HS Code-based Tariff Impact Analysis with DLT 24m
- 08 Streaming Logistics Cost Monitoring with Spark Structured Streaming 26m
- 09 Building the Customs Trade Data Lakehouse & HS Code Validation 18m
- 10 Anomaly Detection for Trade Data and Logistics Costs 26m
- 11 End-to-End Real-time Procurement Price Intelligence 24m
- 12 Comprehensive Testing Strategies for DLT and Streaming Pipelines 27m
- 13 Securing Your Lakehouse with Databricks Unity Catalog 20m
- 14 CI/CD for Databricks Pipelines with Databricks Asset Bundles 25m
- 15 Production Deployment, Monitoring, and Cost Optimization 24m