Microsoft Fabric Beginners: Lakehouse, Notebooks, Power BI

Name: Microsoft Fabric Beginners: Lakehouse, Notebooks, Power BI
Rating: 4.6 (128 reviews)

Get Job-ready Hands-on intro to OneLake, Lakehouse, Warehouse, pipelines, notebooks, Power BI in Microsoft Fabric.

Created byDan We

Last updated 7/2026

English

English [Auto],

What you'll learn

Create a Fabric workspace and start with the Fabric trial
Build Lakehouse and Warehouse items on OneLake
Move and orchestrate data with Dataflows Gen2 and pipelines
Query SQL endpoints and understand Lakehouse vs Warehouse
Run PySpark notebooks and parameterized workflows
Connect Fabric items to Power BI for reporting and automation
Explore real-time scenarios with Real-Time Intelligence, KQL, and Fabric streaming components
Use Git and Azure DevOps version control in Fabric

Course content

3 sections • 68 lectures • 10h 1m total length

Information0:29
Hello and welcome to the the new Microsoft Fabric for beginners course. This section contains all the updated videos. I put a lot of time to update the videos to ensure the best kind of learning experience for you. The "older" videos in the secon section will remain part of the course for a transition period so all students can continue their learning journey without interruption.
My favor to ask. If you enjoy the course and think it is helpful please provide your rating after having finished the course. It is extremely important and helps to keep this course on the platform updated and provide future bonus videos. Appreciate your support :)
Now lets get started together!
Resources0:02
2 Fabric in a nutshell and key terminologies4:16
3 Enable the Fabric Trial capacity2:36
4 Our first tour in the Microsoft Fabric SaaS Platform11:29
Navigate Microsoft Fabric after signing up for the trial via app.fabric.microsoft.com or Power BI, and create a one lake workspace with domains.
5 The Fabric Workspace and important configuration settings10:53
Explore the fabric workspace and create items such as warehouses, lake houses, and notebooks. Manage access with admin, member, contributor, and viewer roles, and explore dataflow gen1/gen2 and git integration.
6 Lakehouse Create your first Fabric Item7:29
Create your first lake house in fabric, enable schemas, upload CSV files, and use the semantic model with Power BI and a read-only SQL endpoint for external queries.
7 Creating Delta tables in Mircosot Fabric Lakehouses6:49
Learn how to create delta tables in Microsoft Fabric lakehouses by loading CSV data into new tables, fixing column names, and using load to table to enable delta querying.
8 Exploring the new Dataflow Gen 2 in Microsoft Fabric18:18
learn to convert csv and excel files into delta tables using Dataflow Gen2 in Microsoft Fabric, configuring lakehouse storage, applying transformations, and publishing the data flow.
9 Fabric Data Pipelines How to use them to create delta tables in Fabric7:07
Learn how to use fabric data pipelines and the new data pipeline to copy data into a lakehouse as delta tables with low-code, no-code steps.
10 Data Pipeline Activities in Microsoft Fabric7:20
11 Exploring the Fabric Lakehouse SQL Endpoint using external tools4:37
Connect to the fabric lakehouse via the SQL analytics endpoint using a connection string in tools like Azure Data Studio to query delta tables in read-only mode.
12 Testing SQL and No Code SQL with the SQL Enpoint in MS Fabric12:04
Connect to the lakehouse read-only SQL endpoint and run queries directly in fabric. Create views, test SQL and no-code SQL workflows, and use the visual query to transform data.
13 Auto Visualizing Data in Fabric with Power BI13:26
Transform your lakehouse data into Power BI visuals inside Microsoft Fabric by creating a semantic model, then auto-generated or manually built reports, explore data, and export reports.
14 Using Microsoft Fabric Items as Power BI Data sources7:56
15 Introduction to Warehouses in Microsoft Fabric16:15
16 Dataengineering Notebook introduction in Microsoft Fabric13:15
Explore data engineering with notebooks in Microsoft Fabric, including attaching lakehouses and loading delta tables. Learn PySpark workflows to clean, transform, visualize, and write results back as delta tables.
17 Pyspark and Pandas examples in MS Fabric Notebooks9:38
Explore PySpark and pandas workflows in MS Fabric notebooks by attaching a lakehouse, loading data from files, transforming with df filters, and writing results to delta tables or files.
18 Parameterized Notebooks with Fabric Data Pipelines16:28
Learn to parameterize a notebook in Fabric by injecting a sheet name from a pipeline, read an Excel file, convert to a PySpark data frame, and write a Delta table.
19 Introduction to Version Control in Microsoft Fabric15:09
Enable git integration for fabric workspaces by connecting Azure DevOps or GitHub, then initialize a local repo, commit changes, and push to the remote repository.
20 Version Control For Power BI Reports in Microsoft Fabric12:02
21 Exploring the Fabric One Lake file explorer the OneDrive for Fabric4:38
Discover the fabric one lake file explorer, a one drive like tool that connects one lake to Windows File Explorer for seamless integration, real-time metadata sync, and local data access.
22 Data Virtualization in MS Fabric Create your first shortcuts7:26
Learn how to use data virtualization in Microsoft Fabric by creating shortcuts to delta tables and files across workspaces and external sources, avoiding data duplication and ETL.
23 Pyspark without Code in Fabric How to use the DataWrangler in MS Fabric12:23
24 Default Python Packages and Environment configuration for Notebooks in Micros12:08
Upload and import custom modules in Microsoft Fabric resources, then configure environments to install libraries from PyPI, including yfinance, across notebooks.
25 Paginated Reports in Microsoft Fabric12:17
Learn to create and customize paginated reports inside Microsoft Fabric, enabling complete exports from Power BI data with page reports, parameters, and flexible styling.
26 Semantik Link in Fabric Using Power BI Semantik Models in Notebooks15:34
Explore semantic link, a Python library in Microsoft Fabric that enables collaboration between Power BI developers, data engineers, and data scientists using a shared semantic model in notebooks.
27 Refresh Power BI semantic models within Notebooks7:20
Refresh Power BI semantic models using semantic link by running a notebook, and configure workspace and dataset, with scheduled or manual refresh options and visibility into refresh history.
28 Realtime Streaming and Eventhouses in Microsoft Fabric14:58
29 The powerful version history attribute of delta tables in MS Fabric14:34
Power Query Tip and Update for Mac Users3:03
Copy multiple Power Query tables between reports by selecting and pasting, then use Power BI service get data to run Power Query in the cloud for Mac users.
Create your own DAX functions in Power BI10:19
Thanks a lot and more to explore0:58

Course resources and helpful links0:07
3 Data Lakehouses in Microsoft Fabric lets create our first one5:44
Create your first lake house in Microsoft Fabric, store tables and files, and use the SQL endpoint to query table data and upload Delta-formatted tables from files.
4 Creating your first delta table in Fabric Lakehouse5:16
Convert a csv file into a delta table in fabric lakehouse, then rename headers to valid names and load the table to enable notebooks and sql queries.
5 How to use Dataflow Gen 2 in Microsoft Fabric8:42
Convert an Excel file to a Delta table in Microsoft Fabric using Dataflow Gen 2, connect to a lakehouse, apply Power Query steps, and publish.
6 Exploring Fabric Data Pipelines8:46
Discover how to build fabric data pipelines, copy data from sources into a lake house, convert files to delta tables, and orchestrate copy and script activities.
7 Querying the Lakehouse Delta tables with external tools4:03
8 A quick Mcrosoft Fabric Workspace Tour5:15
Explore the Microsoft Fabric workspace tour, including lake houses, data flows, pipelines, and the auto-created SQL endpoint and dataset, plus views and Power BI readiness.
9 Creating Power BI Reports with Lakehouse Datasets in Microsoft Fabric8:50
10 Power BI Destkop Reports with Lakehouse as data source7:29
Connect Power BI desktop to a fabric lakehouse via the one lake data hub, then create live or imported reports from published datasets and publish back.
11 Fabric Warehouses Home to Database Admins8:45
Create a fabric warehouse in your workspace and import data with pipelines or SQL queries. Learn to read and write data, use visual or SQL queries, and model table relationships.
12 Fabric Data Warehouse Interacting with the SQL Endpoint with Power BI and Azu7:50
Learn to connect to the Fabric data warehouse with Power BI to build reports. Explore using the SQL endpoint, live connections, and drill down within a hierarchy in reports.
13 Fabric Notebooks for Data Engineers Pyspark and More9:18
Explore how to create and connect PySpark notebooks in Microsoft Fabric, run Spark SQL and Python transformations, and write results as Delta tables in a lakehouse for data engineering workflows.
14 Fabric for Data Engineers Pyspark and Pandas in Fabric 29:46
Bonus How to parameterize a Datapipline and pass Parameters to Notebooks20:31
Parameterize notebooks in fabric by creating a pipeline variable, turning a notebook cell into a parameter, and passing the value to load data and write a delta table.
Trigger Power BI Semantic Model refreshes with Pipeline Activities in Microsoft6:17
15 Fabric Power BI Version Control Setup7:55
Master version control for Power BI using Azure DevOps and Microsoft Fabric by creating a project, cloning a repo, and connecting to a Power BI workspace.
16 Fabric Power BI Version Control Example14:14
Learn how to implement version control in Power BI with Azure DevOps and Git, pushing and pulling P file artifacts for Pokemon reports and datasets.
17 Checking out the new OneLake File explorer3:39
18 Shortcuts in Microsoft Fabric internal and external data sources6:33
Discover how to create shortcuts in Microsoft Fabric to reference internal One Lake warehouses and external data like S3, enabling you to use tables and files without copying data.
19 Helpful features of Fabric Dataflow Gen 210:09
Discover how Fabric dataflow Gen 2 fixes spaces in column names, promotes first-row headers, and exports or imports dataflow templates for reuse in lakehouse workflows.
20 Data Wrangler in Fabric Notebooks for Data Engineers and Data Scientists7:39
Create and connect a Microsoft Fabric notebook to a lakehouse, then use the data wrangler to transform data with spark or pandas, replacing values and dropping columns.
Library and Dependency Management for Microsoft Fabric Notebooks4:05
Learn to manage dependencies in Microsoft Fabric notebooks by creating environments, installing libraries from PyPI or YAML, and publishing to enable automatic use of those libraries.
Modify the Default Dataset of Lakehouses and Warehouses in Fabric Video for DBAs11:03
Modify the default datasets in Fabric warehouses and lakehouses to tailor Power BI reports by removing tables, using SQL endpoints, and creating focused views.
Paginated Reports for Power BI in Mircrosoft Fabric9:06
Create paginated reports in Microsoft Fabric, export complete Power BI table data to PDF or Excel, and add headers and logos in a Fabric lake house workspace.
Using your own custom modules and functions inside Fabric Jupyter Notebooks4:25
Upload your own Python code to Fabric via the Resources section, import the custom module into a notebook, and call its functions like hotdog to reuse proprietary code.
Semantic Link in Fabric Power BI Dataset in Jupyter Notebooks17:02
Explore semantic link in Fabric to read Power BI datasets in a Jupyter notebook, visualize dependencies and relationships, view DAX measures, and collaborate across data analysts and engineers.
How to run Notebooks from other Notebooks in Fabric13:53
Learn how to run a destination notebook from a source notebook in Fabric, passing a table parameter and selectively executing cells with spark utils.
Resources for the next section0:03
Important Note for the next lecture0:14
28 Getting started with Realtime streaming analytics in MS Fabric18:42
29 Realt time Streaming Analytics with your own Data in Microsoft Fabric17:58
Working with Delta Table History in Microsoft Fabric15:12
Explore delta table history in Microsoft Fabric, and learn to update data with SQL or Spark, then rollback to prior versions using version or timestamp.

Requirements

To follow along HANDS ON with the exercises you need a few licenses (free trials available)
You need a Trial License for Fabric (free Trial available)
You need a Power BI License (can be created for free)
For the last exercise Power BI Version control you need Azure DevOps and a code editor installed (e.g. VS Code)
If you don't want to do the excersises and just see the videos you do not need any license at all

Description

Learn Microsoft Fabric from scratch and understand how its core components work together to build modern data workflows.

In this hands-on course, you will create a Lakehouse, move and transform data, and connect everything to Power BI to build a complete end-to-end solution.

This course gives you a structured introduction to Fabric so you can confidently start working with its key features and services.

Learn how to use Microsoft Fabric to build modern data workflows, starting from the fundamentals and progressing to practical, hands-on use cases.

Microsoft Fabric is a unified analytics platform that combines data engineering, data integration, analytics, and business intelligence into a single environment. It brings together services such as Lakehouse, Data Warehouse, Dataflows, Pipelines, and Power BI into one integrated workflow.

This course is designed as a structured introduction. You will start with the basics and then build a complete workflow step by step, learning how the different Fabric components connect and interact.

What makes this course different

This course focuses on understanding how Fabric works as a system, not just as a collection of tools.

You will not only explore individual components like Lakehouse, Warehouse, or Pipelines, but learn how they fit together into a complete data solution.

What you will learn

Create and work with Fabric workspaces and environments
Build and use a Lakehouse for storing and managing data
Understand the difference between Lakehouse and Data Warehouse
Move and transform data using Dataflows Gen2 and Pipelines
Work with PySpark notebooks for data processing
Understand how data flows through Fabric from ingestion to reporting
Connect Fabric data to Power BI for reporting and analysis
Explore key Fabric concepts such as OneLake and integrated data architecture

How you will learn

This course follows a hands-on approach. You will build and explore Fabric components step by step rather than only learning theory.

Each section builds on the previous one, allowing you to understand how the platform works as a complete system.

Additional topics covered

Data integration and transformation concepts
Basic data engineering workflows
Introduction to analytics and reporting in Fabric
Overview of real-time and advanced capabilities

Who this course is for

Beginners who want to learn Microsoft Fabric from scratch
Power BI users who want to understand the broader Fabric ecosystem
Data analysts and professionals who want to explore modern data platforms
Anyone interested in how data engineering, analytics, and BI are combined in Fabric

Who this course is for:

data professionals who want a practical Fabric overview
Power BI users and analysts moving into Fabric

Microsoft Fabric Beginners: Lakehouse, Notebooks, Power BI

What you'll learn

Explore related topics

Course content

The new Microsoft Fabric Course (Video updated)33 lectures • 5hr 13min

archived/reference videos from an earlier Fabric phase32 lectures • 4hr 39min

Bonus3 lectures • 10min

Requirements

Description

Who this course is for: