State of Fabric

A C‑suite view of how Fabric creates measurable enterprise value in 6–12 months. We’ll cover where cost and complexity come out, how decision latency improves, and how to strengthen risk and governance. Includes a practical KPI lens for boards and leadership, investment prioritization, coexistence with current platforms, and proven ways to de‑risk adoption.

The implementation blueprint leaders can trust and practitioners can execute. Walk through end‑to‑end lakehouse design with Direct Lake, semantic layer patterns for Power BI, workspace standards, and Purview‑driven governance and lineage. We’ll address performance tuning, cost control, coexistence with Databricks/Synapse/warehouses, phased migration options, and the roles and operating model that keep delivery on track.

Open Q&A on funding a pilot, governance from day one, security and lineage, change management, and how to align business and technical teams. Bring your use cases; we’ll focus on what’s achievable inside a quarter.

How to bring your existing SQL workloads into Fabric without moving or duplicating data. We’ll cover Fabric Mirroring for operational stores, OneLake Shortcuts to external data, and when to use each. Learn how to expose mirrored/shortcut data to T‑SQL, notebooks, and Power BI; align security (RBAC, sensitivity labels) and governance; understand freshness, latency, and performance trade‑offs; and see a demo that connects an existing SQL application, builds a governed semantic model, and delivers analytics in one place.

Architect AI‑ready analytics by unifying data in OneLake with a trusted semantic layer. We’ll show patterns that ground and orchestrate agentic apps over Fabric (Direct Lake, notebooks, pipelines), integrate responsibly with Azure OpenAI/AI Foundry, and enforce governance with Purview. Includes reference architectures, common integration points with existing platforms, and a walkthrough from data to an AI‑assisted experience.

Bring your architecture questions. We’ll cover coexistence patterns, migration considerations, cost control, performance tuning, and organizational standards. If interest is high, we’ll split short breakouts on AI integration and real‑time analytics.