🌐 Azure Data Engineering Migration Portfolio 👋 Overview
This portfolio showcases three flagship Azure Data Engineering projects demonstrating how cloud-native architectures enable scalable data ingestion, transformation, governance, and executive analytics.
Each case study reflects real-world enterprise scenarios, focusing on:
Cloud migration & modernization
Automated, scalable data pipelines
Analytics-ready datasets
Business-driven KPIs and measurable impact
🏗️ Architecture Patterns Demonstrated
On-prem SQL Server → Azure Cloud Migration
Batch & Incremental Data Processing
Lakehouse Architecture (Bronze / Silver / Gold)
Power BI Semantic Modeling & Executive Dashboards
Secure, governed Azure data platforms
🚀 Project 1: Azure Data Platform for Fleet & Financial Reporting 📌 Overview
End-to-end Azure data platform built to consolidate fleet and financial data into a single analytics layer for executive reporting.
❗ Business Problem
Fragmented on-prem SQL Server databases
Manual reporting processes
Slow turnaround for operational and financial insights
✅ Solution Architecture
Ingestion: Azure Data Factory from on-prem SQL Server
Storage: Azure Data Lake Gen2 (Raw / Curated / Analytics layers)
Transformation: Azure Databricks (Python & SQL)
Analytics: Azure Synapse + Power BI semantic model
📊 Business Impact
Fleet utilization increased to 85.6%
Downtime reduced to 320 hours
Reporting turnaround reduced from 45 hours to under 10 hours
Financial KPIs standardized and reported in ZAR
🔗 View Case Study (Architecture | Code | Dashboard)
📊 Project 2: SQL Server → Power BI Modernization 📌 Overview
Modernization of legacy SQL Server reporting into a scalable, self-service Azure analytics platform.
❗ Business Problem
Manual Excel extracts
Slow refresh cycles
Limited scalability and user access
✅ Solution Architecture
Ingestion: Azure Data Factory
Transformation: Azure Databricks
Analytics Layer: Azure Synapse
Visualization: Power BI with certified datasets
📊 Business Impact
Reporting latency reduced from multiple days to ~12 hours
Active Power BI users scaled to 550+
Financial performance visualized in ZAR
Department-level drilldowns enabled self-service analytics
🔗 View Case Study (Pipelines | Data Model | Dashboards)
⚡ Project 3: Azure Incremental Data Pipeline (Streaming-Style) 📌 Overview
Incremental ingestion pipeline designed for high-volume mobility data using watermark-based processing.
❗ Business Problem
Full dataset reloads increased cost and latency
Delayed insights for operational teams
✅ Solution Architecture
Ingestion: ADF with watermark logic
Processing: Databricks (deduplication & incremental merges)
Analytics: Azure Synapse
Visualization: Power BI near real-time dashboards
📊 Business Impact
Pipeline execution time reduced by 70%
Monthly compute costs significantly reduced (ZAR)
Near real-time operational visibility achieved
🔗 View Case Study (Incremental Logic | Code | Monitoring)
🛠️ Technology Stack Layer Tools Ingestion Azure Data Factory Storage Azure Data Lake Gen2 Processing Azure Databricks (Python, SQL) Analytics Azure Synapse Analytics Visualization Power BI Security Azure AD, Key Vault