Amgad Yassin

Owned and managed the full migration of my department's data infrastructure from Oracle on-premises to Microsoft Fabric cloud, modernizing the data stack for 3,000+ users and unlocking AI capabilities across the organization.

• Migrated 300+ tables with millions of rows from Oracle to Microsoft Fabric using Dataflows, Notebooks, and Pipelines
• Rebuilt entire BI layer — transitioning from MicroStrategy to Power BI, integrating Meta, Google Ads, and GA4 metrics
• Deployed AI & NLP models for customer sentiment analysis and NPS scoring
• Architected Lakehouse & Warehouse environments with automated incremental update pipelines achieving 99.9% data availability
• Built REST APIs to trigger real-time marketing communications
• Developed customer analytics models including RFM analysis and customer personas
• Reduced ETL processing time by 80% via a 5,000+ line SQL model integrating Nielsen data
• Engineered backend database architecture powering a multi-agent AI system

Implemented an enterprise Oracle Digital Experience Platform, integrating a unified 360-degree customer profile across marketing, data, and technology teams.

• Integrated Oracle Unity CDP, Responsys, and Infinity alongside cross-functional teams to build a single 360-degree customer profile
• Orchestrated daily generation and automated delivery of 15+ complex CSV feeds into Responsys via secure file transfers
• Automated marketing data collection from Responsys into the database for Power BI using Python REST APIs
• Built real-time triggers for automated medication dosage reminders
• Deployed automated customer journeys and real-time triggers — directly boosting conversion rates and marketing ROI

Designed and delivered an end-to-end IT Service Management dashboard in Power BI, combining advanced analytics with AI-driven sentiment analysis to optimize service delivery performance.

• Built a complete ETL pipeline extracting and transforming data from Oracle RightNow into a structured analytical model
• Developed advanced DAX measures for SLA tracking, ticket resolution trends, and performance KPIs
• Applied AI & NLP sentiment analysis on customer service interactions to identify pain points
• Enabled data-driven decisions that directly contributed to SLA performance optimization

Capstone project completing the IBM Data Analyst Professional Certificate — applying Python-based data analysis, visualization, and machine learning techniques to a real-world dataset.

A personal end-to-end data analytics project currently in development — showcasing data collection, cleaning, analysis, visualization, and storytelling.