Microsoft Fabric is a complete analytics platform. With multiple engines (Spark, Warehouse, Power BI, etc.) and multiple ways of accessing data (OneLake shortcuts, mirroring, pipelines, etc.) and a focus on implementation of complex decentralized data architectures, it’s imperative to secure data, maintain data provenance, and stay compliant.

When we discuss security in the context of Microsoft Fabric, we categorize security into two broad categories – platform and data. Platform security encompasses security controls related to underlying compute infrastructure, storage, and networking which underpins Fabric.

This session focuses on the data security aspect of Fabric which includes topics related to access controls such as OneLake data access roles, row-level security, workspace access controls, and more.

We take an in-depth look at data security in Microsoft Fabric using features which are currently available across various Fabric engines; scope of each feature; and how to use these controls to secure your data.

We will also discuss various access patterns and how to secure each of these access patterns while following principle of least privilege. We will provide a hands-on look at how to define and use security in Fabric at all levels – workspace security, data security, row and column level security, and more.

We will then switch gears and discuss implementation of complex decentralized architecture such as data mesh using OneLake as the fundamental building block. We will stick to the overarching theme of data security on Fabric and present a perspective on how one can secure data mesh architecture using out-of-the-box features. We will cover aspects such as data discovery, certification, domains, security related to data products.

This session will be in-depth, so bring your laptop and follow along as we show you how OneLake simplifies creating a data mesh architecture.