Mastering Power Bi: Transforming Data Into Insights

Learn Power BI from setup all the way through Power Query, Data Modelling, DAX and Visualizing your data

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.

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.

Overview

Section 1: Introduction

Lecture 1 Course Introduction

Lecture 2 Who This Course Is For

Lecture 3 How To Take This Course

Lecture 4 Motivations & Setting Expectations

Lecture 5 What Is Power BI

Lecture 6 Overview of Power BI Components

Lecture 7 Power BI Licensing

Lecture 8 Fabric SKUs

Lecture 9 Course Overview

Section 2: Download & Install Microsoft Power BI Desktop

Lecture 10 Section Objectives

Lecture 11 Download Option 1

Lecture 12 Download Option 2

Lecture 13 Exploring the Power BI Interface

Lecture 14 Options & Settings

Lecture 15 Power BI Skillsets

Section 3: ETL - Import Mode

Lecture 16 Section Objectives

Lecture 17 Storage Modes - Import

Lecture 18 Direct Query

Lecture 19 Live Connection

Lecture 20 Composite Models & Summary

Lecture 21 Sample Sales Data Overview

Lecture 22 Extract : Ingest Sample Data

Lecture 23 Transform : REPLACE & FILTER

Lecture 24 Transform : SPLIT Column

Lecture 25 Transform : Add Custom Column

Lecture 26 Transform : FILL Down & Column By Example

Lecture 27 Dark Theme

Lecture 28 Transform : GROUP & AGGREGATE Data

Lecture 29 Parameters Example 1 : Dynamic Worksheets

Lecture 30 Parameters Example 2 : Filter Rows

Lecture 31 Parameters Example 3 : Filter Rows Extended

Lecture 32 Power Query Best Practice

Lecture 33 Parameters Example 3 : Data Source From Parts

Lecture 34 Duplicate & Reference

Lecture 35 Transform : Append Sales Data

Lecture 36 Transform : Clean Appended Data

Lecture 37 Transform : Merge Data

Lecture 38 Transform : Merge - Fuzzy Match

Lecture 39 Custom Functions Overview

Lecture 40 Transform : Invoke Custom Function - Example 1

Lecture 41 Your Feedback is Appreciated

Lecture 42 Transform : Custom Function Error Handling

Lecture 43 Extract : Ingest Sample JSON File

Lecture 44 Transform : Invoke Custom Function - Example 2

Lecture 45 Transform : Custom Function Exercise

Lecture 46 Transform : Custom Function Exercise Walkthrough

Lecture 47 Transform : Transpose

Lecture 48 Transform : Unpivot

Lecture 49 Transform : Pivot

Lecture 50 Organize Your Work - Best Practice

Lecture 51 Date Table

Lecture 52 Create Date Table in PowerQuery

Lecture 53 Other Transformations

Lecture 54 Load Data to Power BI Desktop

Lecture 55 Creating Our First Visualizations

Lecture 56 Power Query Data Profiling Tools

Lecture 57 End of Section Summary

Section 4: ETL - Direct Query

Lecture 58 Section Objectives

Lecture 59 Resources

Lecture 60 Connecting to SSMS

Lecture 61 Import 1 Million Rows of Data

Lecture 62 Connect to 1 Million Rows of Data in DQ

Lecture 63 Import Vs DirectQuery - Page Refresh

Lecture 64 Query Folding

Lecture 65 Best Practice for Connecting to Relational Data Sources

Lecture 66 Agggregations

Lecture 67 Data Prep for Aggregations

Lecture 68 Create Aggregation

Lecture 69 Configure Aggregation

Lecture 70 Introduction to Performance Analyzer

Lecture 71 Test Your Aggregation

Lecture 72 Direct Query Summary

Section 5: Dimensional Modelling

Lecture 73 Section Objectives

Lecture 74 Dimensional Modelling

Lecture 75 Fact Tables

Lecture 76 Dimension Tables

Lecture 77 Star Schema

Lecture 78 Kimball's 4 Step Process to Dimensional Modelling

Lecture 79 Normalization

Lecture 80 Denormalization

Lecture 81 Relationships

Lecture 82 Handling Multiple Fact Tables

Lecture 83 Handling Multiple Dates

Lecture 84 Build a Dimensional Model

Lecture 85 Ingest Dimensional Model Data

Lecture 86 Build a Star Schema

Lecture 87 Build Date Dimension Using DAX

Lecture 88 Mark As Date Table

Lecture 89 Create Your Own Dimension Tables and Keys

Lecture 90 Cardinality

Lecture 91 The Flat Table

Section 6: Visualizations

Lecture 92 Section Objectives

Lecture 93 Visualizations

Lecture 94 Clustered Bar & Column Chart

Lecture 95 Stacked Bar & Column Chart

Lecture 96 Stacked vs Column Legend

Lecture 97 Line and Clustered Chart

Lecture 98 Clustered Chart With Two Measures

Lecture 99 100% Stacked Chart

Lecture 100 Line Charts

Lecture 101 Area Charts

Lecture 102 Stacked and 100% Area Charts

Lecture 103 Pie & Doughnut Chart

Lecture 104 Tree Map & Funnel Chart

Lecture 105 Card Visual

Lecture 106 Table Visual

Lecture 107 Matrix Visual

Lecture 108 Scatter Chart

Lecture 109 Slicer Visual

Lecture 110 AI - Decomposition Tree

Lecture 111 AI - Q&A Visual

Lecture 112 A reference to Power BI Visualization Types

Section 7: Data Types & Measure Context

Lecture 113 Section Objectives

Lecture 114 Data Types

Lecture 115 DAX Measures

Lecture 116 Measure Context

Section 8: Implicit & Explicit Measures

Lecture 117 Implicit vs Explicit Measures

Lecture 118 Creating Explicit Measures

Section 9: Creating Measures Table

Lecture 119 Creating a Measures Table

Lecture 120 Alternate to Measures Table

Lecture 121 Hybrid Option for Measures & Folders

Section 10: Calculated Columns & Measures

Lecture 122 Calculated Columns vs Measures

Section 11: Scalar Functions

Lecture 123 Column level vs Iterator Functions

Lecture 124 Column Level Function Scenario

Lecture 125 MAXX Function Example

Section 12: Table Functions

Lecture 126 Table Functions

Lecture 127 SUMMARIZECOLUMNS Virtual Table

Lecture 128 Virtual Table in a Measure

Lecture 129 SUMMARIZECOLUMNS With FILTER

Lecture 130 CALCULATETABLE Part 1

Lecture 131 CALCULATETABLE Part 2

Lecture 132 KEEPFILTERS

Lecture 133 SELECTCOLUMNS

Lecture 134 INTERSECT & EXCEPT

Section 13: Other DAX Functions

Lecture 135 COUNTROWS

Lecture 136 DISTINCTCOUNT

Lecture 137 VALUES Function

Lecture 138 DISTINCT Function

Lecture 139 FILTER Function

Section 14: CALCULATE & Evaluation Context

Lecture 140 Evaluation Context

Lecture 141 Using CALCULATE to Modify Filter Context

Lecture 142 Using ALL & REMOVEFILTERS to Modify Filter Context

Lecture 143 ALL Function

Lecture 144 ALLSELECTED

Lecture 145 ALLEXCEPT

Lecture 146 Introduction to Visual Calculations

Lecture 147 Understanding Context

Section 15: Condition Logic & Relationship Functions

Lecture 148 Create Forecast : Exercise

Lecture 149 IF Conditional Logic

Lecture 150 RELATED Table Function

Lecture 151 Create Forecast Measure

Section 16: Time Intelligence

Lecture 152 Time Intelligence Functions

Lecture 153 SAMEPERIODLASTYEAR

Lecture 154 DATESYTD

Lecture 155 DATESINPERIOD

Lecture 156 DATESBETWEEN

Lecture 157 DATEVALUE

Lecture 158 A reference to time intelligence functions

Lecture 159 Handling Multiple Dates - USERELATIONSHIP

Section 17: Storytelling

Lecture 160 Create Sales by Month Visual

Lecture 161 Highlight Lowest & Highest Data Points

Lecture 162 Screen Size

Lecture 163 Doughnut Chart to Show Percentages Without Measures

Lecture 164 Decomposition Tree

Lecture 165 Field Parameters - Handling Multiple Dimensions

Lecture 166 Field Parameters - Handling Multiple Measures

Lecture 167 Your Task - Create The Finished Report

Lecture 168 My Final Report

Lecture 169 Congratulations

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