Flight Status Dashboard

In this project, I took on the role of a Data Analyst for the Federal Aviation Administration. I worked with a large dataset containing nearly 2 million commercial flights from major U.S. airports. This project focused on uncovering trends and insights related to flight delays and cancellations, empowering stakeholders to make data-driven decisions.

🔍 Project Highlights:

Data Size: Nearly 2 million records, including key flight details from various airports and airlines.

Objective: To create an interactive dashboard for exploring flight delays and cancellations by variables such as airport, airline, and day of the week.

💡 Workflow & Tools:

🔸Data Preparation : Loaded and transformed raw flight data using Power BI’s Power Query.

🔸Data Modeling: Built a relational data model, optimizing data structure for efficient analysis.

🔸Calculated Insights: Added calculated columns and DAX measures to create dynamic visualizations.

🔸Visualization: Designed a user-friendly dashboard to deliver actionable insights and allow users to drill down into specific trends.

Based on the visualizations and metrics shown in this dashboard, here are some key observations, trends, and patterns:

Flight Status Breakdown:

• On-Time Flights: The majority of flights (58%) are on time.
• Delayed Flights: 40.5% of flights are delayed, which is a substantial portion, indicating potential issues in scheduling, airline efficiency, or external factors affecting punctuality.
• Canceled Flights: A small percentage (1.5%) of flights are canceled.

Delayed Flights by Airline:

• United Airlines and Southwest Airlines show the highest delay percentages at 53.5% and 51.4%, respectively. This could indicate operational challenges or external issues disproportionately affecting these airlines.
• Airlines like Hawaiian Airlines and Alaska Airlines have lower delay percentages (around 24%), suggesting they may be more efficient or less affected by delay-inducing factors.

Flight Volume by City:

• Atlanta has the highest number of flights (346,836), followed by Chicago and Dallas-Fort Worth. High traffic in these airports may contribute to delays due to increased demand and potential congestion.

Reasons for Canceled Flights:

• Weather is the leading cause of cancellations, with a significant majority (over 50% of canceled flights).
• Other reasons like Airline/Carrier and National Air System issues also contribute to cancellations but at lower rates.

Cancellation Patterns by Day:

The highest cancellation rate (2.3%) occurs on Day 1, with other days generally ranging from 1.2% to 1.7%. This suggests possible trends in cancellations tied to specific days, which could be due to operational or seasonal patterns.

The final dashboard gives a quick snapshot of on-time, delayed, and canceled flights across different cities and airlines, making it easy for stakeholders to explore and interpret the data effectively. From total flight counts to delayed percentages by airline, each element is tailored for seamless data exploration and decision-making.