Microsoft Fabric OneLake & Databases Full Overview

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In this video, you will learn how Microsoft Fabric data stores work and how they all connect through OneLake, the unified data lake in Microsoft Fabric. We cover the core Fabric analytical data stores including Lakehouse, Warehouse, and Eventhouse, and explain when to use each one in real-world data architectures.

You will also learn the fundamentals of Delta Lake (Delta Parquet), the default table format used across OneLake, and how Fabric separates storage and compute using a serverless capacity-based model. The video explains important Fabric concepts such as Shortcuts, Mirroring, and OneLake availability, and how they help reduce data duplication while enabling near real-time analytics.

In addition, we cover how transactional databases in Fabric differ from analytical data stores, including Fabric SQL Database and Cosmos DB, and how their data is automatically mirrored into OneLake for analytics without impacting application workloads.

What you will learn
Microsoft Fabric data stores overview
OneLake architecture and unified storage model
Delta Lake and Delta Parquet basics
Lakehouse concepts, use cases, and demo
Warehouse concepts, T-SQL support, and demo
Eventhouse for real-time and streaming analytics
KQL fundamentals and Eventhouse limitations
Shortcuts vs mirroring in Microsoft Fabric
Analytical vs transactional databases
Fabric SQL Database and Cosmos DB explained
Automatic mirroring of OLTP data into OneLake

00:00 OneLake
08:45 Lakehouse
21:01 Warehouse
31:23 Eventhouse
45:20 Databases

#microsoftfabric #dp700 #dp600 #OneLake