This repository contains a collection of Power BI dashboards and practice activities focused on business intelligence and data visualization. The project includes various analytical reports and interactive visualizations built using Microsoft Power BI Desktop.
This repository serves as a comprehensive learning and demonstration portfolio for Power BI capabilities, featuring hands-on practice activities and real-world data analysis scenarios. The dashboards showcase data modeling, DAX calculations, and interactive reporting techniques.
- Maven_Cycles_Dashboard.pbix - Primary Maven Cycles business intelligence dashboard
- Advanced_Analytics_Report.pbix - Advanced Power BI data analyst exercises (PL-300 certification prep)
A series of progressive Power BI exercises covering various features and techniques:
| File Name | Focus Area | Skills Covered |
|---|---|---|
| Data_Connection_Basics.pbix | Data Sources | Connecting to Excel, CSV, databases, and web sources |
| Data_Transformation_ETL.pbix | Data Cleaning | ETL processes, data shaping, and query optimization |
| Calculated_Columns_DAX.pbix | DAX Basics | Creating calculated columns and understanding row context |
| Measures_And_KPIs.pbix | DAX Advanced | Building measures, KPIs, and filter context |
| Data_Model_Relationships.pbix | Data Modeling | Star schema, relationships, and cardinality |
| Advanced_Visualizations.pbix | Visualizations | Custom visuals, formatting, and interactive elements |
| Dashboard_Optimization.pbix | Optimization | Query performance, data reduction, and best practices |
- JSON_PBIDS.pbids - Power BI data source connection file
- Microsoft Power BI Desktop - Primary tool for dashboard creation
- DAX (Data Analysis Expressions) - For calculated columns and measures
- Power Query - Data transformation and cleaning
- Data Modeling - Relationship management and schema design
Before using these Power BI files, ensure you have:
- Microsoft Power BI Desktop (latest version recommended)
- Download from: https://powerbi.microsoft.com/desktop/
- Windows 10 or later (Power BI Desktop runs on Windows)
- Basic understanding of data analysis concepts
- Familiarity with business intelligence tools (helpful but not required)
-
Clone the repository
git clone https://github.com/Pravalika1812/Power-BI-Dashboards-Maven-Cycles-Analysis.git cd Power-BI-Dashboards-Maven-Cycles-Analysis -
Install Power BI Desktop
- Download and install from the Microsoft website
- Launch Power BI Desktop
-
Open a Dashboard
- Navigate to the cloned repository folder
- Double-click any
.pbixfile to open it in Power BI Desktop - The dashboard will load with all visualizations and data models
-
Explore Visualizations
- Click on different visual elements to interact with the data
- Use filters and slicers to drill down into specific insights
-
Refresh Data (if connected to live sources)
- Click "Refresh" in the Home ribbon
- Update data source credentials if prompted
-
Modify Reports
- Switch to "Edit" mode to customize visualizations
- Add new charts, tables, or KPIs as needed
- Interactive Dashboards - Dynamic filtering and cross-highlighting
- Data Modeling - Properly structured star/snowflake schemas
- DAX Calculations - Custom measures and calculated columns
- Visual Design - Professional layouts and color schemes
- Performance Optimization - Efficient queries and data loads
This project analyzes business metrics for a cycling company, including:
- Sales performance tracking
- Product category analysis
- Geographic distribution of sales
- Time-series trends and forecasting
- Customer segmentation insights
Each learning file focuses on specific Power BI skills:
Beginner Level:
Data_Connection_Basics.pbix- Master various data source connectionsData_Transformation_ETL.pbix- Learn ETL and data cleaning techniques
Intermediate Level:
Calculated_Columns_DAX.pbix- Create calculated columns using DAXMeasures_And_KPIs.pbix- Build complex measures and KPIsData_Model_Relationships.pbix- Design effective data models
Advanced Level:
Advanced_Visualizations.pbix- Create stunning visualizationsDashboard_Optimization.pbix- Optimize dashboard performance
This repository follows a structured learning approach:
- Beginner: Basic data connections, Power Query, and simple visuals
- Intermediate: Data modeling, DAX formulas, and advanced visuals
- Advanced: Complex calculations, optimization, and certification prep
- Clean and efficient data models
- Proper use of relationships (1:many, many:many)
- Optimized DAX formulas for performance
- User-friendly dashboard layouts
- Consistent color schemes and branding
- Effective use of bookmarks and drill-through pages
Problem: Dashboard won't open or shows errors
- Solution: Ensure you're using a compatible version of Power BI Desktop
Problem: Data refresh fails
- Solution: Update data source credentials in Power Query Editor
Problem: Visualizations appear blank
- Solution: Check data source connectivity and refresh the dataset
Problem: Slow performance
- Solution: Reduce data volume, optimize DAX queries, or remove unnecessary columns
The Advanced_Analytics_Report.pbix file aligns with Microsoft's PL-300: Power BI Data Analyst certification exam objectives.
Contributions, issues, and feature requests are welcome! Feel free to:
- Fork the repository
- Create a feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Pravalika - @Pravalika1812
Project Link: https://github.com/Pravalika1812/Power-BI-Dashboards-Maven-Cycles-Analysis
This project is available for educational and portfolio purposes. Please respect intellectual property rights when using or sharing these materials.
- Maven Analytics for inspiration and datasets
- Microsoft Power BI team for excellent documentation
- Power BI community for continuous learning resources
Interactive dashboard showing sales performance, revenue trends, and key business metrics
Shows annual sales volume trends across UK regions, highlighting growth and regional contribution patterns.
Geospatial visualization displaying regional sales distribution across the UK using location-based insights.
Waterfall chart illustrating how year-over-year regional changes drive overall sales increases and decreases.
📝 Note: Screenshots showcase the interactive Power BI dashboards created in this project. These demonstrate data visualization techniques, DAX calculations, and business intelligence best practices.
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