Training Days 2026
Build a Lakehouse in a Day with Metadata and Open-Source Tools
Paul Andrew & Matt Collins
Unlock the power and speed of a metadata-driven Lakehouse architecture.
In the fast-paced, data-driven world, the ability to swiftly and efficiently deliver a robust data platform is key to maintaining a competitive edge. Join us for an immersive, full-day hands-on workshop, where we will guide you through the process of building a metadata-driven Lakehouse using the open-source product framework, known as CF.Cumulus. Leveraging and abstracting Microsoft cloud native technologies to ease delivery challenges.
During this workshop, participants will get an in-depth understanding of how CF.Cumulus can integrate Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Microsoft Fabric and other resources to streamline data insight deliveries.
Our expert instructors will provide practical insights on overcoming common data challenges, including fragmented data ingestion, change data capture, and orchestration scalability, using our proven best practices.
Attendees will learn how to utilise metadata, open-standards, and seamless cloud integration to accelerate time-to-insight with minimal technical debt, ensuring cost control and operational resilience. This workshop is ideal for both data engineers and data leaders who are looking to enhance their cloud data platform delivery and unlock the potential to build a Lakehouse in a day using a metadata driven approach.
Big Data in Power BI: Handling billions of rows with great performance
Denis Selimovic
Your data has exploded. You either cannot even import the amount of data anymore, if you can import it, it takes for ever and DirectQuery is super slow. Reports timeout and users are complaining. You're stuck with a problem that you're not sure how to solve.
But there are solutions for really big amounts of data.
Power BI and Microsoft Fabric offer multiple proven strategies to handle billions of rows efficiently. The challenge is knowing which approach to use and when.
What You'll Learn
This full-day training covers every major architectural pattern for extreme-scale data:
- Storage modes compared: Import, DirectQuery, and DirectLake and when to use each
- DirectLake in action: Combining Import speed with DirectQuery freshness
- KQL for performance: Lightning-fast queries on massive datasets
- Databricks Mirroring: Leveraging computational power while keeping Power BI reporting
- Aggregate tables done right: Pre-aggregation strategies that rescue struggling models
Through live demos with billion-row datasets, performance comparisons, and hands-on exercises, you'll build decision frameworks to architect the right solution for your scenarios.
Walk Out Ready
Leave with proven patterns, real-world strategies, and the confidence to handle massive data volumes in Power BI, no more compromising between speed and scale.
Setup to Deployment: A full day of CI/CD for Microsoft Fabric using DevOps
Kev Chant & Sander Stad
When looking to implement CI/CD within Microsoft Fabric using Azure DevOps one of the biggest questions is where to start, due to the various options available. In this hands-off PreCon we will explore the various CI/CD (Continuous Integration and Continuous Deployment) options available when working with Microsoft Fabric and Azure DevOps.
Participants will gain fresh insights into different CI/CD workflow options, including:
- An introduction to Git and branching strategies when working with Microsoft Fabric Git integration
- Microsoft Fabric Deployment Pipelines
- Performing Git-based deployments
- Deploying with Azure Pipelines.
- Tooling's such as fabric-cicd and Fabric CLI
- How to perform automated tests for various Fabric items
- Working with variable libraries
- Alternative deployment methods for Microsoft Fabric Data Warehouses and SQL Databases in Fabric
By the end of the session, attendees will have a comprehensive understanding of the various CI/CD options available when looking to implement CI/CD for Microsoft Fabric using Azure DevOps. So that they can decide on the best way forwards.