📊 Power BI for Data Analytics - Full Course

Data Nerds! This repo contains all the files needed to follow along my free course: Power BI for Data Analytics

⚠️ Download from Google Drive, not GitHub! Some files are missing here due to GitHub's 100MB limit. Get complete course files from Google Drive

Team Members 👥

🙋🏼‍♂️ Course Leader: Luke Barousse
🎬 Course Producer: Kelly Adams
📺 Video Editor: Brannon Linder

Table of Contents

📚 Course Modules

• 1. Grand Tour - Introduction to Power BI App and Dashboard Building

  • 1.1 PBI App Intro
  • 1.2 Dashboard Build

• 2. Visualizations - Core Chart Types and Visual Elements

  • 2.1 Visualizations

• 3. Power Query - Data Transformation and ETL

  • 3.1 Power Query Intro
  • 3.1 Power Query Intro (BigQuery Demo)
  • 3.2 Power Query Editor
  • 3.3 Project2 Import
  • 3.4 Advanced Transformations
  • 3.5 Append
  • 3.5 Merge
  • 3.6 M Language

• 4. DAX - Data Analysis Expressions

  • 4.1 DAX Intro
  • 4.2 Explicit Measures
  • 4.3 Parameters

🎯 Projects

• Project 1: Data Jobs Dashboard - Comprehensive two-page dashboard

  • Features: Market overview, drill-through analysis, interactive filtering
  • 📊 Dashboard File
  • 🌐 View Interactive Dashboard

• Project 2: Data Jobs Dashboard 2.0 - Single-page focused dashboard

  • Features: Streamlined insights, advanced DAX, star schema modeling
  • 📊 Dashboard File
  • 🌐 View Interactive Dashboard

📊 Data Sources

• Data Folder - Real-world 2024 data science job postings
  • 📄 job_postings_flat.csv - Single table format
  • 📊 job_postings_monthly.xlsx - Monthly breakdown
  • 📁 monthly_files/ - Individual monthly Excel files
  • 📁 star_schema_files/ - Normalized star schema format

🧩 Practice Problems

• Problems Folder - Hands-on exercises with solutions
  • Organized by module (1_Grand_Tour, 2_Visualizations, 3_Power_Query, 4_DAX)
  • Includes problem files and solution files
  • Practice datasets included

📁 Additional Resources

• Resources Folder - Supporting materials
  • Project screenshots and GIFs
  • Example dashboards
  • Course images and assets

How to Run Power BI Files

📋 Prerequisites

• Power BI Desktop (Free) - Download from Microsoft Power BI
• Power BI Service Account (Free tier available) - For publishing and sharing dashboards
• Microsoft Excel (Optional) - For viewing data files

🚀 Getting Started

1. Download Power BI Desktop

• Visit Microsoft Power BI Desktop download page
• Download and install the latest version (free)
• Sign in with your Microsoft account when prompted

2. Open Course Files

1. Navigate to the desired module folder (e.g., 1_Grand_Tour/, 2_Visualizations/, etc.)
2. Double-click any .pbix file to open it in Power BI Desktop
3. If prompted, click "Enable Content" to allow data connections

3. Working with Data Files

• CSV Files: Can be opened directly in Power BI Desktop using "Get Data" → "Text/CSV"
• Excel Files: Use "Get Data" → "Excel Workbook" to import
• Monthly Files: Import individual files or use folder import for batch processing

📁 File Types Explained

Data Files

• job_postings_flat.csv: Single table with all job data
• job_postings_monthly.xlsx: Multi-sheet Excel file organized by month
• monthly_files/: Individual Excel files for each month
• star_schema_files/: Normalized database structure (4 separate tables)

🔧 Troubleshooting

Common Issues

• "Enable Content" Dialog: Always click "Enable Content" when opening .pbix files
• Data Source Errors: If data connections fail, check the file paths in Power Query
• Missing Visuals: Ensure all required data fields are loaded and relationships are established

Data Connection Issues

• If you encounter data source errors:
  1. Go to Home → Transform Data → Data Source Settings
  2. Update the file paths to match your local directory structure
  3. Click "Change Source" and navigate to the correct data files

Performance Tips

• Large Datasets: Use filters in Power Query to reduce data size
• Refresh Issues: Close and reopen Power BI Desktop if refresh fails
• Memory: Close other applications if Power BI runs slowly

💡 Pro Tips

• Save Frequently: Power BI Desktop files can be large - save often
• Use Bookmarks: Create bookmarks to save different views of your data
• Test Interactions: Always test slicers, filters, and drill-through features
• Performance: Use measures instead of calculated columns when possible
• Documentation: Use the "About" section in your reports to document data sources and methodology

Found a Typo? Want to Contribute?

• If you find an error in this repo, please feel free to make a pull request by:
  • Forking the repo
  • Making any changes
  • Submitting a pull request