Intermediate3 daysMost popular

Microsoft Fabric & OneLake

End-to-end data analytics on a unified platform

Overview

Microsoft Fabric unifies data engineering, data warehousing, data science, real-time analytics, and business intelligence into a single SaaS platform. This hands-on training takes you from OneLake architecture through to working pipelines, lakehouses, and Power BI reports — all within one environment.

What you'll learn

  • Understand the Fabric architecture and how OneLake centralises all data
  • Create and manage lakehouses, warehouses, and data pipelines
  • Ingest and transform data using Data Factory and Dataflows Gen2
  • Build semantic models and Power BI reports directly in Fabric
  • Apply row-level security and workspace governance best practices
  • Integrate with Azure Data Lake Storage and existing Azure resources

Programme

Day 1 — Fabric architecture & OneLake
  • What is Microsoft Fabric and how it compares to traditional stacks
  • OneLake: the single data lake for your entire organisation
  • Workspaces, capacities, and licensing explained
  • Creating your first lakehouse and uploading data
  • Delta Lake format: why it matters and how Fabric uses it
  • Hands-on: set up a Fabric workspace from scratch
Day 2 — Data engineering & integration
  • Data Factory in Fabric: pipelines, activities, and triggers
  • Dataflows Gen2: low-code data transformation with Power Query
  • Notebooks with PySpark: data engineering at scale
  • Connecting external sources: databases, APIs, cloud storage
  • Incremental loads and watermark patterns
  • Hands-on: build an end-to-end ingestion pipeline
Day 3 — Analytics, BI & governance
  • Fabric Data Warehouse: T-SQL analytics over lakehouse data
  • Direct Lake mode: Power BI without import or DirectQuery overhead
  • Building semantic models and calculated measures in DAX
  • Row-level security and object-level security
  • Monitoring, lineage, and audit logs in Fabric
  • Hands-on: publish a governed Power BI report from lakehouse data

Who is this for?

  • Data engineers building or modernising data platforms
  • BI developers moving from legacy tools to Fabric
  • Data architects evaluating Fabric for enterprise adoption
  • IT managers responsible for data infrastructure decisions

Prerequisites

  • Basic understanding of SQL and relational data concepts
  • Familiarity with cloud concepts (Azure experience is a plus)
  • No prior Fabric experience required

Tools & technologies covered

Microsoft FabricOneLakePower BIData FactoryPySparkDelta LakeT-SQL
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