Building a semantic model should not feel like starting from scratch every time. Yet many organizations still rely on manual processes that are difficult to maintain, scale, and recover when changes are made.
In this session, you'll discover how Microsoft Fabric enables a more standardized approach to semantic models, helping teams reduce repetitive work, improve consistency, and accelerate the delivery of trusted business insights.
Rather than focusing on individual models, we'll explore how semantic models can be treated as reusable and scalable assets. You'll learn why metadata, naming conventions, standardized date tables, and automation are becoming increasingly important in a world of AI-powered analytics and Data Agents.

Semantic models should become repeatable, maintainable, and scalable assets instead of manually crafted one-off solutions.

During this session you will see the following benefits.
• Understand why standardization is essential for scalable semantic models.
• Learn how metadata improves discoverability, governance, and AI readiness.
• See how automation reduces maintenance effort and increases consistency.
• Discover how semantic models can evolve from one-off solutions into reusable business assets.

Audience: Data professionals, BI developers, analytics engineers, and Fabric practitioners interested in scaling semantic models.
Prerequisites: Basic knowledge of semantic models and Power BI/Fabric concepts.