Name: Power BI Desktop Essentials - Beginner to Advanced
Rating: 4.5 (1 reviews)

Udemy Business

Teach on Udemy

Turn what you know into an opportunity and reach millions around the world.

Learn More

Your cart is empty.

Keep shopping

Created byManpreet Singh Ragi

Last updated 4/2026

English

What you'll learn

Navigate and utilize the Power BI interface to connect to data sources, build reports within the Power BI ecosystem.
Describe the different storage modes available in Power BI and understand the strengths and weaknesses of each mode.
Learn how to use Power Query and the M language to cleans and transform your data
Describe the process and importance of data modelling using industry recognized approaches
Establish relationships between tables and understand the implications of cardinality, filter propagation, and model performance.
Write DAX formulas to create calculated columns and measures, apply logic, perform aggregations, and implement advanced time intelligence functions.
Apply BI skills to real-world business scenarios through guided projects that simulate common use cases like sales tracking, performance analysis.
Build knowledge & skills needed to pass the PL-300 Exam

Course content

17 sections • 169 lectures • 12h 47m total length

Course Introduction1:43
Who This Course Is For1:19
How To Take This Course2:15
Motivations & Setting Expectations2:27
What Is Power BI0:45
Overview of Power BI Components2:44
After completing this lecture students will have an understanding of the components that make up the Power BI platform.
Power BI Licensing4:56
After completing this lecture students will have an understanding of the different license types available for Power BI and the key differences in price and features.
Fabric SKUs0:27
Course Overview5:59
Power BI is a reporting tool

Section Objectives1:35
In this students will learn about the section objectives.
Storage Modes - Import3:34
In this lecture students will learn about the different storage modes in Power BI and start of with the details of Import mode.
Direct Query3:09
In this lecture students will gain an understanding of the behaviour of DirectQuery mode.
Live Connection3:37
Composite Models & Summary1:33
Sample Sales Data Overview2:05
Extract : Ingest Sample Data14:22
In this lecture students will ingest the supplied sample file and get started with transforming.
Transform : REPLACE & FILTER3:45
Transform : SPLIT Column3:26
In this lecture students will learn how to split a column by delimiters in order to derive desired results.
Transform : Add Custom Column2:35
In this lecture students will learn how to create a new column based on custom logic.
Transform : FILL Down & Column By Example6:06
In this lecture students will learn how to use the column by example functionality to derive desired results.
Dark Theme0:48
Transform : GROUP & AGGREGATE Data5:35
In this lecture students will learn about the basics of grouping and aggregating data.
Parameters Example 1 : Dynamic Worksheets9:54
In this lecture students will learn how make Excel worksheets dynamic to easily switch sources.
Parameters Example 2 : Filter Rows3:46
Parameters Example 3 : Filter Rows Extended3:43
In this lecture students will learn how to filter rows dynamically using other parameters in M code.
Power Query Best Practice4:00
In this lecture students will learn about some best practices around renaming Power Query steps for understandability.
Parameters Example 3 : Data Source From Parts6:16
In this lecture students will learn how they can use parameters to form dynamic file paths from multiple parts.
Duplicate & Reference3:43
In this short lecture students will learn about the difference between duplicating and refencing datasets.
Transform : Append Sales Data5:40
In this lecture students will learn about how to combine data using the append functionality.
Transform : Clean Appended Data14:23
In this lecture student will learn how to clean and align data after appending two datasets.
Transform : Merge Data7:30
In this lecture students will learn about the merge functionality.
Transform : Merge - Fuzzy Match13:03
This lecture will walkthrough how to implement the fuzzy matching look up and use a mapping table to look up values which fall outside of fuzzy matching.
Custom Functions Overview3:01
After this lecture students will have a high level understanding of custom functions in Power Query and their pros and cons.
Transform : Invoke Custom Function - Example 17:40
Your Feedback is Appreciated0:13
Transform : Custom Function Error Handling2:19
Extract : Ingest Sample JSON File3:13
Transform : Invoke Custom Function - Example 28:00
In this lecture students will see another example of invoking a custom function.
Transform : Custom Function Exercise2:09
Transform : Custom Function Exercise Walkthrough6:36
Transform : Transpose2:37
In this lecture students will learn the basic of the Transpose function in PowerQuery
Transform : Unpivot2:06
Transform : Pivot3:20
Organize Your Work - Best Practice11:54
In this lecture students will learn the best practices for organizing their work in Power Query
Date Table3:01
Create Date Table in PowerQuery5:24
Other Transformations4:39
Load Data to Power BI Desktop5:52
In this lecture student will learn how to load data back to Power BI and some considerations when loading data to help you optimize your semantic model
Creating Our First Visualizations8:10
In this lecture students will create the very first visuals from the same sales data.
Power Query Data Profiling Tools10:04
In this lecture students will about the profiling tools available in Power Query to help understand and validate your data.
End of Section Summary0:54
ETL Quiz

Section Objectives1:11
Resources0:05
Connecting to SSMS7:06
Import 1 Million Rows of Data6:10
In this lecture students will learn about how Import mode could perform with 1 millions rows of data
Connect to 1 Million Rows of Data in DQ5:51
In this lecture student will see how DirectQuery responds to 1 Million rows of data
Import Vs DirectQuery - Page Refresh7:18
In this lecture students will see how DirectQuery can reflect latest changes to underlying data through page refresh while Import mode would require a table or model refresh.
Query Folding4:44
In this lecture students will learn about query folding and how to identify this in Power Query.
Best Practice for Connecting to Relational Data Sources5:04
In this lecture students will learn the best practice for connecting to a relation data source.
Agggregations2:37
In this lecture students will learn about about aggregations and how we can use them to overcome performance challenges when using Direct Query against a large dataset.
Data Prep for Aggregations1:41
In this lecture students will learn how to prepare your data for aggregations and how to apply best practice methods to connect to the data source using views.
Create Aggregation2:15
In this lecture students will learn how to create aggregations.
Configure Aggregation6:30
In this lecture students will learn how to configure aggregations.
Introduction to Performance Analyzer2:01
In this lecture students will learn about the basics of performance analyzer and how to trace queries.
Test Your Aggregation6:56
In this lecture student will learn how to use / test their aggregations to ensure they are working correctly.
Direct Query Summary7:25
Direct Query Quiz

Section Objectives1:01
In this section students will learn about the principles of dimensional modelling.
Dimensional Modelling0:58
Fact Tables7:10
Dimension Tables5:03
Star Schema3:55
Kimball's 4 Step Process to Dimensional Modelling4:19
Normalization4:14
In this lecture students will learn about normalization in database terms.
Denormalization3:08
In this lecture students will learn about denormalization.
Relationships4:59
In this lecture students will learn about the different relationship types.
Handling Multiple Fact Tables3:17
Handling Multiple Dates2:52
Build a Dimensional Model6:19
In this lecture students will be introduced to a sample dataset which they will use to build a dimension model in Power BI.
Ingest Dimensional Model Data9:38
Build a Star Schema9:15
Build Date Dimension Using DAX6:55
Mark As Date Table4:29
Create Your Own Dimension Tables and Keys6:00
In this lecture students will learn how to create your own dimension if ever needed and how to generate your own unique ID/Key values and use them between Facts and dimension tables.
Cardinality3:58
In this lecture students will learn about what is cardinality and how it can affect your data model.
The Flat Table7:12
In this lecture students will learn about the challenges of using a flat data table as a model.
Data Modelling Quiz

Section Objectives1:27
Visualizations1:40
Clustered Bar & Column Chart7:20
Stacked Bar & Column Chart3:28
Stacked vs Column Legend1:05
Line and Clustered Chart3:53
Clustered Chart With Two Measures1:01
100% Stacked Chart3:30
Line Charts5:07
Area Charts1:55
Stacked and 100% Area Charts1:39
Pie & Doughnut Chart4:06
Tree Map & Funnel Chart2:57
Card Visual2:43
Table Visual3:06
Matrix Visual4:11
Scatter Chart7:19
Slicer Visual6:01
AI - Decomposition Tree8:06
AI - Q&A Visual8:50
A reference to Power BI Visualization Types0:02
Visualization Quiz

Requirements

No prior experience with Power BI is needed as we'll learn everything from scratch but any familiarity with data is always useful

Description

Unlock the power of data with "Mastering Power BI: Transforming Data into Insights" — a comprehensive, hands-on course designed to take you from foundational knowledge to advanced proficiency in Microsoft Power BI.

Whether you're a business analyst, data professional, or aspiring BI developer, this course provides the skills and confidence you need to transform raw data into actionable insights.

Starting with Power Query, you’ll learn how to import, clean, and shape data, building efficient preparation workflows. Along the way you will learn about the different storage modes available and be able to contrast between them. You will also explore aggregations in Power BI and learn how to use these to overcome performance challenges.

A special emphasis is placed on Dimensional Modeling — a technique used to structure data into fact and dimension tables for efficient querying and user-friendly analytics. You'll explore star and snowflake schemas, learn how to identify facts and dimensions and implement these models in Power BI to support self-service analysis and accurate performance measurement.

The course then progresses into DAX (Data Analysis Expressions) — the formula language of Power BI. You’ll learn how to write DAX to perform dynamic calculations, create time intelligence metrics, understand evaluation context and drive interactivity in your reports.

Throughout the course, theory is balanced with practical, real-world tasks that reinforce learning. You will solve common business problems, and complete a guided project that simulates actual reporting challenges.

By the end, you’ll have a deep understanding of the end-to-end BI workflow.

No prior experience in Power BI is required, but familiarity with Excel or basic data concepts is helpful.

This course will also help you build the knowledge and skills needed to pass the PL-300 certification.

Who this course is for:

This course is ideal for business analysts, data professionals, Excel users, managers, and anyone looking to turn data into actionable insights using Power BI.

What you'll learn

Explore related topics

Course content

Introduction9 lectures • 23min

Download & Install Microsoft Power BI Desktop6 lectures • 32min

ETL - Import Mode42 lectures • 3hr 35min

ETL - Direct Query15 lectures • 1hr 7min

Dimensional Modelling19 lectures • 1hr 35min

Visualizations21 lectures • 1hr 19min

Data Types & Measure Context4 lectures • 13min

Implicit & Explicit Measures2 lectures • 10min

Creating Measures Table3 lectures • 9min

Calculated Columns & Measures1 lecture • 8min

Requirements

Description

Who this course is for: