Power BI: Beginner to Intermediate – Data Science Academy

About Course

Course Overview

Duration: 40-45 hours (8-9 weeks at 5 hours/week)
Level: Beginner to Intermediate
Prerequisites: Basic Excel knowledge, familiarity with data concepts
Target Audience: Business analysts, data analysts, report developers, and professionals transitioning to BI roles

Course Objectives

By the end of this course, students will be able to:

Navigate Power BI Desktop and Service confidently
Import and transform data from multiple sources
Build effective data models with proper relationships
Create interactive visualizations and dashboards
Write fundamental to intermediate DAX formulas
Publish and share reports securely
Implement best practices for report design and performance

Course Schedule (Sample 9-Week Plan)

Week 1: Modules 1-2 (Introduction and Data Connection)
Week 2: Module 3 (Power Query Transformation)
Week 3: Module 4 (Data Modeling)
Week 4: Module 5 (Introduction to DAX)
Week 5: Module 6 (Visualizations)
Week 6: Module 7 (Interactivity) + Mid-term Project
Week 7: Module 8 (Intermediate DAX)
Week 8: Module 9 (Power BI Service)
Week 9: Module 10 (Best Practices) + Final Project

Tips for Success

Practice Daily: Spend 30 minutes daily working with Power BI
Build Real Projects: Use your own data or work scenarios
Join Community: Participate in Power BI Community forums
Watch Recordings: Review class recordings for complex topics
Ask Questions: No question is too small in office hours
Document Learning: Keep notes on DAX formulas and techniques
Experiment: Try different visualizations for same data

Next Steps After This Course

After completing this course, students will be ready for:

Power BI Advanced Course (DAX Advanced, Advanced Analytics)
Microsoft PL-300 Certification preparation
Real-world Power BI implementation projects
Specialization in specific industries or use cases

Master the Power BI Ecosystem:
Navigate the full workflow: Desktop, Service, and Mobile.
Understand the critical difference between "loading data" and "modeling data."
Gain the confidence to install, configure, and manage your Power BI environment.
Transform "Dirty" Data into Clean Insights:
Stop manual copy-pasting. Learn to automate data cleaning using Power Query.
Merge, append, and unpivot complex datasets from Excel, CSVs, and folders.
Build a robust data pipeline that refreshes with a single click.
Build the "Brain" of Your Report (Data Modeling):
Move beyond flat Excel tables. Learn to build the professional Star Schema.
Master relationships (One-to-Many) and troubleshoot common connectivity errors.
Create dynamic Date Tables to unlock powerful time-based analysis.
Unlock Deep Analysis with DAX:
Write your first measures using the industry-standard DAX language.
Calculate complex metrics like "Year-over-Year Growth," "Running Totals," and "Variance %."
Understand the "Why" behind the code: Context, Aggregation, and Calculation logic.
Design "App-Like" Interactive Reports:
Create professional visuals: Bar charts, Maps, KPIs, and Matrix tables.
Implement advanced UX (User Experience) features like Bookmarks, Drill-throughs, and Page Navigation.
Tell a data story using Tooltips and conditional formatting that highlights key trends automatically.
Publish & Share with Confidence:
Deploy your reports to the secure Power BI Cloud Service.
Configure automatic data refreshes so your dashboard is always up-to-date.
Learn the best practices for sharing insights via PDF, PowerPoint, and secure links.

Course Content

Module 1: Introduction to Power BI (4 hours)

1.1 What is Power BI and its business value

24:29
1.2 Power BI Desktop vs Power BI Service vs Power BI Mobile

16:17
1.3 Power BI licenses: Free, Pro, Premium, Premium Per User

17:43
1.4 Understanding workspaces and capacity

17:19
1.5 Power BI architecture and workflow

24:33
1.6 Installing and configuring Power BI Desktop and Understanding the ribbon and navigation panes

13:03
1.7 Report view, Data view, and Model view

06:13
1.8 Saving and file management (.pbix files) & create Power BI Template (.pbit)

05:13
1.9 Loading a sample dataset

08:49
1.10 Creating basic visualizations

10:23
1.11 Adding filters and slicers

05:25
1.12 Formatting basics

08:44
1.13 Lab Exercise: Build your first dashboard

50:15
1.14 Open Power BI Template

03:53
1.15 Publishing to Power BI Service

04:32

Module 2: Data Connection and Import (5 hours)

Module 3: Power Query and Data Transformation (8 hours)

3.1 Understanding the Power Query environment

19:46
3.2 Removing and keeping rows/columns

09:59
3.3 Changing data types

09:03
3.4 Splitting and merging columns

10:43
3.5 Replacing values and finding/replacing

08:21
3.6 Filling down and up

03:47
3.7 Removing duplicates

02:12
3.8 Pivoting and unpivoting data

06:52
3.9 Transposing tables

02:13
3.10 Grouping and aggregating data

05:58
3.11 Conditional columns

05:31
3.12 Custom columns with formulas

05:31
3.13 Index columns and ranking

08:57
3.14 Append queries (union)

06:47
3.15 Merge queries (joins): Inner, Outer, Left, Right

10:09
3.16 Understanding join types and scenarios

09:25
3.17 Expanding and aggregating merged data

06:38
3.18 Query dependencies

06:00
3.19 Lab Exercise: Project 1 Sales Performance Capstone

01:13
3.20 Lab Exercise: Project 2 HR & Payroll Analytics

01:27
3.21 Module 3 Reference

01:27

Module 4: Data Modeling (6 hours)

4.1 Star schema vs snowflake schema

06:25
4.2 Fact tables vs dimension tables

06:56
4.3 Primary keys and foreign keys

07:23
4.4 Normalization principles for Power BI

07:41
4.5 Best practices for model design

08:55
4.6 Creating and managing relationships

11:10
4.7 Cardinality: One-to-Many, Many-to-One, One-to-One

10:37
4.8 Cross-filter direction: Single vs Bi-directional

08:02
4.9 Active vs inactive relationships

09:52
4.10 Relationship troubleshooting

06:09
4.11 Creating date hierarchies

12:55
4.12 Building custom hierarchies

05:08
4.13 Organizing fields into display folders

06:46
4.14 Hiding and showing fields

02:42
4.15 Configuring data categories

05:47
4.17 Lab Exercise: Build a complete star schema model

09:49

Module 5: Introduction to DAX (7 hours)

5.1 What is DAX and why it matters

11:56
5.2 Calculated columns vs measures

08:42
5.3 DAX syntax and operators

08:05
5.4 Understanding row context vs filter context

06:59
5.5 Basic data types in DAX

06:11
5.6 Aggregation functions: SUM, AVERAGE, MIN, MAX, COUNT

12:07
5.7 CALCULATE function introduction

12:28
5.8 ALL and FILTER basics

17:15
5.9 Text functions: CONCATENATE, LEFT, RIGHT, MID

10:59
5.10 Date functions: YEAR, MONTH, DAY, DATEDIFF, TODAY, NOW

06:45
5.11 Logical functions: IF, AND, OR, SWITCH

15:20
5.12 Lab Exercise: Create 10 essential calculated measures

44:25
5.13 CALENDAR and CALENDARAUTO functions

06:08
5.14 Basic time intelligence: TOTALYTD, TOTALQTD, TOTALMTD

10:06
5.15 Year-over-year calculations: SAMEPERIODLASTYEAR

05:21
5.16 Period-to-date comparisons

04:34
5.17 DATEADD for flexible time comparisons

08:39
5.18 Lab Exercise: Build a complete time intelligence framework

Module 6: Visualizations – Fundamentals (6 hours)

Data Visualization introduction

05:12
6.1 Bar and column charts: when to use each

03:12
6.2 Line and area charts for trends

04:04
6.3 Pie and donut charts (when appropriate)

05:29
6.4 Tables and matrices

03:54
6.5 Cards and multi-row cards

04:35
6.6 Gauges and KPIs

07:35
6.7 Scatter plots and bubble charts

05:19
6.8 Maps: filled maps, shape maps, ArcGIS

04:01
6.9 Treemaps and waterfall charts

04:27
6.10 Funnel charts

07:25
6.11 Ribbon charts

07:36
6.12 Custom visuals from AppSource

13:05
6.13 Choosing the right chart type

05:30
6.14 Color theory and accessibility

05:49
6.15 Formatting for clarity

06:51
6.16 Tooltips and drillthrough

07:59
6.17 Conditional formatting

08:20
6.18 Lab Exercise: Redesign a poor dashboard using best practices

50:40

Module 7: Interactivity and Filters (2 hours)

Module 8: Intermediate DAX (4 hours)

8.1 Understanding filter context modification

08:57
8.2 Multiple filter arguments

09:39
8.3 CALCULATE with ALL, ALLEXCEPT, ALLSELECTED

06:24
8.4 Using CALCULATE for percentage calculations

12:34
8.5 CALCULATE vs CALCULATETABLE

11:05
8.6 RELATED function for lookup values

04:51
8.7 RELATEDTABLE for aggregations

07:06
8.8 USERELATIONSHIP for inactive relationships

06:14
8.9 SUMX, AVERAGEX, COUNTX, MINX, MAXX

10:56
8.10 Advanced Conditional Logic (The SWITCH Function)

07:04
8.11 Ranking and Top-N Analysis

08:10

Module 9: Power BI Service (4 hours)

9.1 Understanding workspaces

10:14
9.2 Workspace roles and permissions

08:23
9.3 Publishing reports from Desktop to Service

10:47
9.4 Creating and Managing workspace

06:28
9.5 Sharing dashboards and reports

06:35
9.6 Apps and app audiences

07:20
9.7 Creating and using apps

07:39
9.8 Comments and collaboration features

09:50
9.9 Subscription and alerts

09:36
9.10 Row-level security (RLS) implementation

07:55
9.11 Scheduled refresh configuration

03:13
9.12 Incremental refresh concepts

13:06
9.13 Incremental refresh

08:47

Module 10: Report Design and Best Practices (4 hours) – Reading articles
Please download the PDF and read the article

10.1 Information hierarchy and layout
10.2 White space and visual balance
10.3 Consistent formatting and branding
10.4 Mobile-first considerations
10.5 Accessibility guidelines (color blindness, screen readers)
10.6 Query folding and optimization
10.7 Reducing data model size
10.8 Measure optimization techniques
10.9 Visual performance tips
10.10 Using Performance Analyzer
10.11 Documenting data sources and transformations
10.12 Naming conventions for measures and columns
10.13 Version control considerations

Module 11: The Job-Ready Portfolio (Real-World Projects)

Module 12: BONUS MODULE: Power BI Interview Questions & Answers
Download the PDF for each lesson

Lesson 12.1: Interview Preparation Fundamentals (30-40 min)
Lesson 12.2: Beginner Level Questions (Modules 1-2) (45-60 min)
Lesson 12.3: Power Query and Data Transformation Questions (Module 3) (50-60 min)
Lesson 12.4: Data Modeling Questions (Module 4) (50-60 min)
Lesson 12.5: DAX Fundamentals Questions (Module 5) (60-75 min)
Lesson 12.6: Advanced DAX Questions (Module 8) (60-75 min)
Lesson 12.7: Visualization and Design Questions (Modules 6-7, 10) (45-60 min)
Lesson 12.8: Power BI Service and Administration Questions (Module 9) (45-60 min)
Lesson 12.9: Scenario-Based and Troubleshooting Questions (60-75 min)
Lesson 12.10: Behavioral and Soft Skills Questions (40-50 min)

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About Course

Course Overview

Course Objectives

Course Schedule (Sample 9-Week Plan)

Tips for Success

Next Steps After This Course

What Will You Learn?

Course Content

Module 1: Introduction to Power BI (4 hours)

1.1 What is Power BI and its business value

1.2 Power BI Desktop vs Power BI Service vs Power BI Mobile

1.3 Power BI licenses: Free, Pro, Premium, Premium Per User

1.4 Understanding workspaces and capacity

1.5 Power BI architecture and workflow

1.6 Installing and configuring Power BI Desktop and Understanding the ribbon and navigation panes

1.7 Report view, Data view, and Model view

1.8 Saving and file management (.pbix files) & create Power BI Template (.pbit)

1.9 Loading a sample dataset

1.10 Creating basic visualizations

1.11 Adding filters and slicers

1.12 Formatting basics

1.13 Lab Exercise: Build your first dashboard

1.14 Open Power BI Template

1.15 Publishing to Power BI Service

Module 2: Data Connection and Import (5 hours)

2.1 File-based sources (Excel, CSV, JSON, XML)

2.2 Database connections (SQL Server, MySQL, PostgreSQL)

2.3 Online Services (SharePoint)

2.4 Web data and APIs

2.5 Other Power BI datasets

2.6 Import vs DirectQuery vs Live Connection

2.7 Using the Navigator interface

2.8 Managing Data Connections ,credentials and Refreshing

Module 3: Power Query and Data Transformation (8 hours)

3.1 Understanding the Power Query environment

3.2 Removing and keeping rows/columns

3.3 Changing data types

3.4 Splitting and merging columns

3.5 Replacing values and finding/replacing

3.6 Filling down and up

3.7 Removing duplicates

3.8 Pivoting and unpivoting data

3.9 Transposing tables

3.10 Grouping and aggregating data

3.11 Conditional columns

3.12 Custom columns with formulas

3.13 Index columns and ranking

3.14 Append queries (union)

3.15 Merge queries (joins): Inner, Outer, Left, Right

3.16 Understanding join types and scenarios

3.17 Expanding and aggregating merged data

3.18 Query dependencies

3.19 Lab Exercise: Project 1 Sales Performance Capstone

3.20 Lab Exercise: Project 2 HR & Payroll Analytics

3.21 Module 3 Reference

Module 4: Data Modeling (6 hours)

4.1 Star schema vs snowflake schema

4.2 Fact tables vs dimension tables

4.3 Primary keys and foreign keys

4.4 Normalization principles for Power BI

4.5 Best practices for model design

4.6 Creating and managing relationships

4.7 Cardinality: One-to-Many, Many-to-One, One-to-One

4.8 Cross-filter direction: Single vs Bi-directional

4.9 Active vs inactive relationships

4.10 Relationship troubleshooting

4.11 Creating date hierarchies

4.12 Building custom hierarchies

4.13 Organizing fields into display folders

4.14 Hiding and showing fields

4.15 Configuring data categories

4.17 Lab Exercise: Build a complete star schema model

Module 5: Introduction to DAX (7 hours)

5.1 What is DAX and why it matters

5.2 Calculated columns vs measures

5.3 DAX syntax and operators

5.4 Understanding row context vs filter context

5.5 Basic data types in DAX

5.6 Aggregation functions: SUM, AVERAGE, MIN, MAX, COUNT

5.7 CALCULATE function introduction

Module 10: Report Design and Best Practices (4 hours) – Reading articles
Please download the PDF and read the article