Wednesday 1:45 PM - 2:45 PM · B405-B406a

Transition from Data Analyst to Data Engineer: Upgrading Skills from DataFlows Gen2 to Notebooks

The session shows an analyst how to use notebooks to perform the same actions as Dataflow Gen2. Looking at 4 areas: source, transformation, cleansing, and destination, examples include append/merge query to dataframe joins, text replace functionality, split and concatenate columns, as well as pivot/unpivot, data type changes, and removing duplicates. We will finish off with engine optimizations.

Wednesday 3:05 PM - 4:05 PM · TMB 1

Materialized Lake Views: Simplifying Your Medallion ETL

Materialized lake views turn Spark SQL into auto-orchestrated smart tables in your Fabric lakehouse. In this session, learn how to replace fragile ETL with declarative medallion layers, understand refresh and lineage, and decide when materialized lake views beat notebooks, jobs, or warehouses.

Wednesday 4:25 PM - 5:25 PM · C111-C112

CORENOTE: Fabric Data Engineering Roadmap

Fabric Data Engineering empowers data engineers to build out a lakehouse architecture and transform their data, at scale, using Spark. Join this session to learn more about the latest updates to Data Engineering in Fabric, as well as what's coming in the near future.

Wednesday 4:25 PM - 5:25 PM · B313b-B314

Config-Driven Data Engineering in Microsoft Fabric

Data-engineering often results in hundreds of one-offs with duplicate code and inconsistency, making change slow, brittle, and costly. We will introduce and demo new metadata and config-driven patterns for PySpark integration in Fabric. You will learn to implement reusable patterns that simplify development, scale reliably, cut duplication, and improve governance across Fabric environments.

Thursday 8:00 AM - 9:00 AM · C211-C213

Spark Performance Deep Dive: Configuration, Debugging, and Performance Tuning

Unlock the full potential of Apache Spark with this in-depth session focused on performance optimization. We’ll explore advanced configuration strategies to fine-tune executors, memory, and partitioning for maximum efficiency. Learn how to leverage Spark’s built-in tools for debugging and monitoring, including the Spark UI and metrics, to identify bottlenecks and optimize workloads.

Thursday 8:00 AM - 9:00 AM · C301

Enterprise-Grade Migration to Microsoft Fabric: Modernizing Lakehouses, Pipelines, Analytics & AI

Microsoft Fabric is rapidly becoming the unified platform of choice for enterprises seeking to modernize data engineering, analytics, and AI. But migration from Synapse, ADF, Snowflake, Databricks, and on-prem systems requires more than a lift-and-shift.

Thursday 9:30 AM - 9:50 AM · Expo Innovation Theater

Transform your data platform into an AI-ready foundation for growth

Modernize your end-to-end data platform to Fabric and unlock AI/ML enabled potential in workloads, analytics, and collaboration. During this session, we will focus on agentic AI methods of automation during the migration process, achieving 60% improvement in productivity.

Thursday 10:10 AM - 11:10 AM · B312-B313a

Delta Lake in Fabric: Internals, Innovations, and What’s New in Delta 4.0

From Delta 4.0 to Microsoft’s latest runtime innovations, dive into how Delta features really work. Learn Liquid Clustering and when to use it, why file size matters and how to put table tuning on autopilot, how to compact tables dramatically faster, and much more. Leave a time-traveling Delta Lake wizard ready to build fast, flexible, and scalable tables that deliver high-performance at any scale

Thursday 10:10 AM - 11:10 AM · C301

Unity in Action – Building Enterprise AI on a Unified Semantic Foundation

Enterprise AI requires unified semantic foundations where governance and intelligence flow seamlessly. Learn to architect data platform that use Ontology as your semantic backbone, Data Agents for insights, and Operational Agents for action. Through real-world examples, discover how organizations use AI agents to reliably detect, contextualize, attribute, and act on governed data.

Thursday 11:30 AM - 12:30 PM · C108-C109

Adapting to Fabric Spark: A SQL Server Practitioner’s Path Forward

This workshop is for SQL Server practitioners, used to reading query plans and caring about stats, stepping into Fabric. It covers Lakehouses and Spark, showing how your skills still apply in:

• Understanding the Spark engine
• Reading query plans and statistics
• Using the Delta Lake engine

The takeaway is that approaches might differ, but the knowledge carries over.

Thursday 2:00 PM - 3:00 PM · C113-C114

Best Practices for Library Management with Microsoft Fabric Spark Environments

Managing Python and JAR library dependencies is key to building reliable, performant, and maintainable Spark workflows.

Learn how to ensure reproducibility through consistent dependency handling, use lightweight setups to accelerate development and testing, enable inline installs for ad-hoc workloads, and integrate private repositories for secure, compliant library management.

Thursday 2:00 PM - 3:00 PM · C102

Fabric Development: Repos, Collaboration and Deployments

Are you a Fabric developer and struggling with using good development practices? Implementing practices such as source code control, branching strategies, code reviews (PRs), and automated deployments to independent environments (ie. workspaces) can transform how you work with Fabric. We'll show how to implement them and work around the gotchas that will bite you in your Fabric projects.

Thursday 4:15 PM - 5:15 PM · TMB 4

Agentic Copilot in Fabric Notebooks

Discover how agentic Copilot transforms Fabric notebooks into a proactive, context-aware assistant. Learn how it empowers users with transparent reasoning, guided troubleshooting, and adaptive workflows, boosting productivity while preserving human control.

Thursday 4:15 PM - 5:15 PM · C105-C106

Own Your Workflow: Build Notebooks Locally & Deploy Them to Fabric

Break free from browser IDE in Fabric Python and PySpark Notebooks! Learn to install Python and Spark, create your own local lakehouse, and develop Python and PySpark Notebooks in Visual Studio, VSCode, or whatever IDE you're used to. We'll start with a clean machine and download, install and configure everything we need. We will create a feature-rich notebook, and wrap up by deploying to Fabric.

Friday 10:10 AM - 11:10 AM · C211-C213

Microsoft Fabric Essentials: No-Code to Pro-Code with Dataflows Gen2

Microsoft Fabric Dataflows Gen2 empowers everyone to prepare data efficiently. In this session, learn no-code steps for quick wins, low-code techniques with Power Query for flexibility, and pro-code customization with M for full control. Discover practical strategies to simplify data prep and enable governed, reusable data at scale.

Friday 11:30 AM - 12:30 PM · C113-C114

Mastering Fabric Data Engineering Admin and Capacity Management

Optimize Microsoft Fabric Data Engineering for production. Learn about governance controls for Notebooks, Lakehouses, and Spark Job Definitions. We'll cover administrative roles, capacity management for cost and performance, and scaling best practices.

Friday 11:30 AM - 12:30 PM · C202-C204

Patterns and Best Practice with Fabric CI/CD

This session teaches best practices with Fabric GIT integration to ensure changes to Fabric projects are automatically tested and deployed, leading to faster and more reliable releases. Attendees will learn effective branching strategies for merging changes from feature workspaces into production.

Friday 2:00 PM - 3:00 PM · C102

Beyond Monitoring: AI-Driven Spark Optimization in Microsoft Fabric

Join this demo by Microsoft AI and Spark experts to see how Fabric takes Spark observability to the next level! Learn how to stream Spark logs to Eventhouse using Diagnostic Emitter. See Fabric AI/ML tooling in action to detect bottlenecks, predict resource impact, and suggest code improvements to optimize performance and cost. Visualize the insights and recommendations in Real Time Dashboard.

Friday 3:15 PM - 4:15 PM · C108-C109

Demystifying Spark Profile Optimizations in Microsoft Fabric

Optimizing Spark workloads in Microsoft Fabric can be a complex endeavor, given the array of available configurations and techniques. Terms like V-Order, Z-Order, and considerations for read-heavy versus write-heavy profiles often add to the confusion. In this session, we'll bring clarity to these concepts, offering a structured overview of each optimization strategy.​