Fundamentals of Microsoft Fabric

Part II. The Features: A Deep Dive

In this section, we’ll go through all the experiences in Microsoft Fabric—Fabric’s core features—explaining what each one does and how it works.

We’ll break down each experience with step-by-step guidance and real-world examples, showing you how to apply it effectively. This will help not only in understanding the experiences’ technical workings but also in seeing their practical value for solving data challenges. The key experiences we will explore include:

Data Factory

The orchestration and data movement engine of Fabric, enabling pipelines and ETL/ELT processes

Data Engineering

A powerful environment for working with large-scale data processing, optimized for Spark workloads

Data Warehousing

A fully managed, scalable solution for building structured, analytical data stores

Data Science

Tools and workflows designed for machine learning, model training, and AI-powered analytics

Real-Time Intelligence

A framework for processing streaming data, enabling immediate insights and decision making

Power BI

The analytics and visualization powerhouse of Fabric, allowing interactive reporting and dashboards

SQL Databases

Fabric’s answer to bridging the gap between analytical and OLTP workloads

Mirroring

A capability for syncing and managing external data sources within Fabric without complex data movement

GraphQL

An API layer for querying and interacting with data in a flexible and efficient way

AI and Copilots

AI-driven assistants ...