Ivana Pejeva

Fabric Data Agents can query your semantic models, but can they truly understand your business? Semantic models describe the shape of your data, but they don't capture meaning. That missing layer is an ontology. This session exposes where agents break down and introduces practical patterns for enriching your semantic layer with ontological metadata: business glossaries, concept hierarchies, relationship semantics, and inference rules. Through live demos, you'll see how these enrichments help Data Agents resolve ambiguity, reason across domains, and produce trustworthy answers. You'll leave with a maturity framework and a concrete roadmap to get from "semantic model" to "knowledge layer" without boiling the ocean.

In the wild world of machine learning, it's essential to stay on top of model and data drift to keep your models running smoothly. In this presentation, we'll show how to use Azure Machine Learning to do MLOps and how you can track and tame these sneaky beasts. We'll explore the concepts and importance of MLOps, the challenges it presents, and the best practices. Through a series of real-world examples and hands-on demonstrations, we'll show you how to use Azure Machine Learning to identify and overcome drift, so your models can continue to thrive in the jungle of machine learning.

To enable scalable data engineering in the Modern Data Platform on Azure, we could use Synapse and/or Databricks, SQL & Spark and data science. In this session, we will clarify how Azure Synapse compares with Databricks and share for which use-case Synapse or Databricks is a better choice. This session includes a demo which demonstrates the similarities or differences between the tools.

This session will show how we can use Azure Databricks as a fully managed service by Microsoft to train and tune our machine learning models. Additionally, I will demonstrate how Data Factory can be used to automate & schedule the whole process of starting and stopping a cluster, training the model and saving it to a blob storage. During the session I will cover the following subjects: What is Azure Databricks? What is Azure Data Factory? How can we use them together to train our ML models? The presentation will be followed by a short demo.