Model Smarter, Not Harder: Fabric’s New Era of Semantic Models Empowerment

Let’s be honest, manually building and maintaining semantic models takes way too much time and effort. And when configurations are deleted on purpose, having to rebuild everything from scratch is just frustrating. In this session, we’ll show how to automate semantic model deployment using only native Fabric tooling. The goal? Model smarter, not harder! With less manual work, more consistency, and a super simple way to build and empower a semantic model creation. Plus enable insights with a Data agent!

During this session you will see the following benefits.
• Use the power of XMLA endpoints (Same logic for SSAS, Azure Analyses Services and Power BI / Fabric models)
• Always add time intelligence in one go with a standardized approach. (Standaard date table)
• Use naming conventions for automation purposes to retrieve better value out of the data agents.
• Stil be able to adjust manual sections for your customer definitions.
• Seeing the value of standardizing date tables for time intelligence
What more could you ask for?!
• Understand the lifecycle of semantic models in Fabric.
• Understand the importance of Metadata for generation models and metrics.
• Seeing the value of standardizing date tables for time intelligence
• Flexibility & Scalability

Audience:
Technical People looking for automation they did not find out yet, with a slightly business focus as well.
Prerequisites:
Knowledge of Semantic models, DAX , Python & Notebooks.

Medallion Magic: Turning Data Layers into Stories That Stick

Ever wondered why every data platform follows a hidden pattern? Meet the Medallion Architecture: the secret behind all data architectures. Do you remember classic BI solutions? Or data layers like Cleansed or Curated?
In this session, discover why you’ve been using it all along, how to apply it intentionally, and turn everyday about your data platform into stories that connect and inspire.
Based on real‑world experience, this session will help you:
Recognize the Medallion pattern in both modern data platforms and classic BI architectures
Understand the business purpose of Bronze, Silver, and Gold layers
Translate technical data layers into clear business value
Use the Medallion Architecture as a storytelling framework to align business and IT stakeholders
By the end of the session, you’ll see why the Medallion Architecture feels so familiar, and find the secret behind all data architectures.
What more could you ask for? Stick to the plan, and you will get there!

This session is designed for a broad, business‑oriented audience:
Data Engineers, Business Analysts, and Managers, anyone involved in data decisions who wants conceptual clarity without deep technical detail.
Prerequisites:
No prior knowledge of Medallion Architecture is required.
Complexity: 100 (Business - Overview) / 200 (Intermediate)

Model Smarter, Agent Better: Powering Fabric Data Agents with Intelligent Semantic Models

AI is only as good as the data model behind it.
In Microsoft Fabric, the semantic model is no longer just a reporting layer: it’s the brain of your Data Agent.

In this session, we’ll show how generated, well structured semantic models become the key enabler for powerful, reliable Data Agents. You’ll see how automating semantic model generation creates the consistency, metadata richness, and governance that agents need to reason correctly, answer business questions, and scale across use cases.

From there, we’ll move into Data Agent API creation, demonstrating how semantic models are exposed as intelligent, reusable interfaces for AI-driven insights. Finally, we’ll elevate the story with Fabric IQ, showing how adding clear instructions and intent dramatically improves agent behavior, trust, and business value.

Model smarter, so your agents can work harder.

What you’ll see:
Semantic models at scale: why generated models are crucial for reliable Data Agents
Fabric IQ in action: guiding agents with context for better answers

A full demo:
From generated semantic model to an API deployed Data Agent.
You'll see why With Fabric IQ will gain you business insights!

Key takeaways
Why semantic models are foundational for trustworthy AI
How metadata quality drives agent intelligence
How Fabric IQ turns AI from “working” into “valuable”
How to scale AI‑driven analytics with consistency

Audience & prerequisites
For Data & Analytics professionals and architects building AI‑ready platforms.
Basic knowledge of Semantic Models, DAX, and Microsoft Fabric assumed.

From Data to Meaning: Unlocking Business Value with Ontologies in Fabric IQ

Many organizations have centralized their data in Microsoft Fabric and built semantic models, yet still struggle to create a shared understanding of what the data actually means for the business.

This is where ontology models in Fabric IQ provide the missing foundation.
In this session, we explore how Fabric IQ places ontology at the center of the data platform, turning fragmented models into a governed and reusable semantic foundation. Ontologies enable a single source of truth, support cross-domain analytics, and create a connected knowledge layer.

You will see how ontologies bring together semantic models, graphs, and Data Agents, ensuring that all components operate on a shared business definition.
As a result, ontologies become the backbone of intelligent data platforms, ensuring that insights and AI-driven interactions are consistent, explainable, and aligned with the business.

In Fabric IQ, ontology turns data into meaning, and meaning into action.

What you’ll learn
- Understand and recognize when to apply an ontology
- Explain how ontology models capture business meaning using entities, relationships, and rules, with examples
- Recognize the role of ontology within Fabric IQ alongside semantic models, graphs, and Data Agents
- Apply ontology concepts to design more consistent, reusable, and AI-ready data platforms

Technical Requirements
- Basic understanding of Microsoft Fabric (Lakehouse, Warehouse, or Power BI semantic models)
- Familiarity with data modeling concepts (tables, relationships, business definitions)
- No prior experience with Fabric IQ or ontologies required

Audience
This session is designed for Microsoft Fabric practitioners, including Data Engineers, Analytics Engineers, AI Engineers, and Architects.
Anyone designing data platforms, semantic models, or AI-driven solutions who wants to introduce more business context and meaning into their data.