Data Analyst | SQL | Power BI
📊 Project Control & Execution Monitoring Dashboard
Power BI · Data Modeling · DAX · Business Intelligence
⬇ Download Dashboard PDF🚧 Business Problem
- Project data scattered across multiple Excel sheets
- No visibility of delays and execution status
- Manual tracking and reporting inefficiency
- No centralized dashboard for decision-making
💡 Solution Approach
- Centralized Power BI dashboard
- DAX-based execution tracking logic
- Aging analysis for delay tracking
- KPI-based layout for quick insights
🧹 Data Preparation
- Project Master
- Project Execution
- Documentation Register
- TDS Register
📊 Key Dashboard Features
📈 Key Insights
- Identified delayed and overdue tasks
- Detected execution bottlenecks
- Improved project visibility
- Enabled faster decision-making
🧰 Tools & Technologies
🤖 AI-Assisted Development
This dashboard was developed with AI assistance to improve structure, DAX logic, and visualization design. Final implementation and business validation were handled manually.
📊 Project Control & Execution Monitoring Dashboard
Tools Used: Power BI · Excel · Data Modeling · DAX
This dashboard was designed to monitor project execution, identify delays, track documentation progress, and provide real-time visibility into operational performance.
🚧 Business Problem
- Project data was scattered across multiple Excel sheets
- No centralized visibility of task progress and delays
- Difficult to track execution status (On Track / In Progress / Delayed)
- Manual reporting caused delays in decision-making
- No clear view of documentation status and pending dependencies
💡 Solution Approach
- Built a centralized Power BI dashboard for project monitoring
- Created structured data model from multiple Excel sources
- Developed DAX logic for execution status (On Track / Delayed / In Progress)
- Implemented aging analysis for execution tracking
- Designed KPI-driven layout for quick decision-making
🧹 Data Preparation & Modeling
Raw data was initially unstructured and distributed across multiple sheets. To improve performance and usability, the data was cleaned and transformed into separate structured tables:
- Project Master – Project-level information
- Project Execution – Task tracking and execution details
- Documentation Register – Document status tracking
- TDS Register – Additional operational data
Relationships were created between tables to enable accurate reporting and filtering.
📊 Key Dashboard Features
- ✔ KPI Cards for Total Projects, Pending Tasks, Overdue Tasks, and Missed Targets
- ✔ Execution Status Tracking (On Track, In Progress, Delayed)
- ✔ Project Completion Progress (Donut Visualization)
- ✔ Task Status Distribution Analysis
- ✔ Execution Analysis by Discipline
- ✔ Aging Bucket Analysis (0-7, 8-15, 16-30, 30+ Days)
- ✔ Dependency Tracking (Pending with Client, Purchase, Design)
- ✔ Interactive Filters (Client Name, Date Range)
📈 Key Insights Generated
- Identified high number of overdue and delayed tasks
- Highlighted departments with lower execution performance
- Detected bottlenecks in approval and dependency stages
- Improved visibility of project completion status
🤖 AI-Assisted Development
This dashboard was developed with the assistance of AI tools to:
- Design the dashboard layout and structure
- Optimize DAX calculations and logic
- Improve data modeling approach
- Enhance visual storytelling and user experience
Final implementation, validation, and business logic were manually handled to ensure accuracy.
🧰 Tools & Technologies
- Power BI
- DAX
- Excel
- Data Modeling
- Business Intelligence
This project demonstrates my ability to transform raw data into actionable business insights using Power BI.