This project was created by following the Power BI tutorial from the YouTube video below:
🔗 YouTube Tutorial: https://www.youtube.com/watch?v=E1ux-bi3CBc
This project is an Air Quality Index (AQI) Analysis Dashboard created using Microsoft Power BI to analyze air pollution data across different cities and states.
The dashboard transforms raw environmental data into clear and interactive visual insights, helping users understand pollution levels, identify major pollutants, and observe AQI trends over time.
The objective of this project is to demonstrate how data visualization tools like Power BI can help analyze environmental conditions and support data driven decision making.
The dataset used in this project includes air quality measurements collected from different locations.
| Field | Description |
|---|---|
| City | Name of the city where AQI is recorded |
| State | State in which the city is located |
| AQI | Air Quality Index value |
| Pollutant | Primary pollutant detected |
| Date | Date of AQI observation |
| Category | AQI classification such as Good, Moderate, Unhealthy |
This dataset allows analysis of pollution distribution, pollutant frequency, and AQI trends over time.
A gauge visualization displays the AQI level for the selected state and categorizes pollution severity.
Categories include:
- Good
- Moderate
- Unhealthy
- Poor
- Very Unhealthy
- Hazardous
A bar chart identifies the cities with the highest AQI levels, helping highlight areas experiencing severe pollution.
A donut chart shows how AQI values are distributed across different pollution categories.
This helps understand the overall environmental condition across locations.
A chart analyzes the frequency of pollutants such as:
- PM10
- PM2.5
- CO
- O3
- NO2
This helps identify which pollutants contribute most to poor air quality.
A line chart tracks AQI levels across months and years to identify pollution trends and seasonal variations.
A map visualization shows AQI values geographically across states to easily identify high pollution regions.
This project demonstrates multiple Power BI features including:
- Data cleaning and transformation
- Interactive dashboard creation
- Filters and slicers
- Map visualizations
- Gauge charts
- Donut charts
- Bar charts
- Line charts
- Data aggregation
These techniques help transform complex datasets into easy to interpret visual insights.
| Component | Description |
|---|---|
| AQI Gauge | Displays the AQI level |
| Top Cities Chart | Shows most polluted cities |
| Map Visualization | Displays AQI by state |
| AQI Category Distribution | Breakdown of pollution levels |
| Pollutant Frequency | Most common pollutants |
| AQI Trend Chart | AQI changes over time |
| Filters | Year, State, and City selection |
Users can interact with filters to explore specific locations or time periods.
Through this project, the following skills were developed:
- Creating interactive dashboards in Power BI
- Understanding environmental datasets
- Applying data visualization techniques
- Transforming raw data into meaningful insights
This project reflects the type of analysis performed by data analysts and business intelligence professionals.
Possible improvements for the project include:
- Adding AQI prediction models
- Integrating real time pollution data
- Expanding analysis with more cities and states
- Building an advanced analytics dashboard