Frederic Van Kelecom

Microsoft Fabric provides a unified data platform for customers to build solutions on - and this extends to ISVs as well. In this session we will discuss some of patterns, practices and considerations for ISVs building apps on Fabric. These patterns, practices, and considerations are inspired by our collaboration with top ISVs across industries who are developing applications on Fabric. As part of this we will look into two common use-cases 1) Modernizing SQL reporting solutions to Fabric 2) Lakehouse and Spark-centric data access solutions In this session we will cover: 1 - options for customer isolation and tenancy considerations 2 - managing network access, authentication and authorization in common ISV solutions 3 - automation options for ISVs to enable scalable, repeatable and reliable deployments. 4 - logging and auditing concerns in an ISV scenario 5 - integration Apps built on Fabric with the Fabric Workload Extensibility SDK 6 - different options for enabling customer access to data from a range of applications

By now you’ve probably heard lots about Microsoft Fabric, the latest and greatest SaaSified analytics solution from Microsoft. In a nutshell, Fabric enables you to work on a single copy of data using your favourite analytical engine. Whether you want to write good old SQL queries, do advanced data engineering using Spark notebooks or you just want to create a report in Power BI, Fabric has you covered. This is all possible through OneLake, the next chapter in the data lake storyline. I hear you thinking “how does that work/perform?”, “does it integrate with other technologies?”, “what are some of the gotcha’s?” ... In this advanced session we’ll answer all these questions and instantly transform you into a OneLake expert! We will dive deep into the technology it’s built on, giving you a technical breakdown of the key features whilst also addressing some of the things you need to be aware of before plunging in! Specifically, we will cover: - Brief overview of the evolution of data lakes - Distinctive features that set OneLake apart, focusing on: - file format - shortcuts - DirectLake - Hands-on demo illustrating its usability and performance - Current limitations and unsolved feature mysteries - How to start working with OneLake The session is designed for data engineers and data analysts who have a fundamental knowledge of Azure data services and want to get a deeper technical understanding of Microsoft Fabric’s OneLake.