Session Abstract

Modern enterprises are rapidly adopting Microsoft Fabric to unify data engineering, analytics, data science, and business intelligence into a single SaaS platform. However, designing an enterprise-scale Fabric implementation requires more than simply migrating workloads—it demands a well-architected approach to scalability, governance, security, and performance.

In this session, attendees will learn how to build production-ready enterprise data platforms using Microsoft Fabric. We will explore proven architectural patterns, OneLake design, medallion architecture, data ingestion strategies, Lakehouse and Warehouse integration, Real-Time Intelligence, Data Factory pipelines, and semantic modeling with Power BI. The session will also cover performance optimization techniques, cost management strategies, governance with Microsoft Purview, and security best practices for large-scale deployments.

Drawing from practical implementation patterns and real-world engineering experience, this session provides actionable guidance for designing scalable, resilient, and high-performing data platforms that support analytics, AI, and enterprise reporting workloads.