🌟 Optimizing MCO’s Holiday Operations: A Data-Driven Analysis of December 2024 Flight Traffic 📊✈️🎉

Matias Rossi
Apr 27
4 min read

Orlando International Terminal, Florida, USA

🎈 My journey into analyzing domestic flight arrivals at Orlando International Airport (MCO) during December 2024 was an exhilarating dive into Orlando’s tourism magic, powered by Disney World and Universal Resorts! 🎢🌴🎄 I crafted a seamless workflow to transform raw flight data into actionable insights, empowering MCO to enhance operations and elevate passenger experiences during the holiday rush. 🎁 This project showcases my skills in data extraction, relational schema design, SQL querying in SQL Server Management Studio (SSMS), data visualization, and reporting. Join me on this data adventure! 🚀🌟😊

🎯 Project Objective

🚀 The mission was to dissect inbound domestic flight patterns at MCO in December 2024, uncovering traffic trends, airline performance, and operational challenges to deliver recommendations that optimize staffing, gate allocation, and passenger services, harnessing Orlando’s tourism hub status during a bustling holiday season. 📈✨

🛠️ Detailed Process

🎉 My workflow unfolded like a story, each step building on the last to craft meaningful insights for MCO. From sourcing data to presenting polished recommendations, every stage played a vital role in turning raw numbers into operational strategies.

📂 Starting with the Data

🎊 I began by exploring the Bureau of Transportation Statistics (BTS) website, where a wealth of domestic flight data awaited. On the BTS interface, I filtered the dataset by state (Florida), month (December), and year (2024) to focus on flights relevant to MCO’s holiday season. I selected key columns like flight dates, delays, cancellations, airline codes, and origin cities to create a focused dataset. To ensure accuracy, I verified row counts (~30,000 flights) and key fields (e.g., flight numbers) against BTS metadata, laying a solid foundation for the journey ahead. 🔍✅😊

🏗️ Crafting the Database Blueprint

🎨 With data in hand, I envisioned a relational database schema to organize it efficiently, designing three tables to structure the information:

Flights: Captured flight details like flight number, date, delay minutes, and cancellation status. ✈️
Airports: Stored origin city and state data. 🌍
Airlines: Held carrier names and codes. 🛩️

I chose data types such as DATETIME for dates, VARCHAR(50) for city names, and BIT for cancellations, linking tables with primary and foreign keys (e.g., airline code in Flights referencing Airlines). An Entity-Relationship Diagram (ERD) brought this structure to life, serving as a roadmap to enable complex queries and ensure data integrity for MCO’s analytical needs. 📐🌟

💻 Building the Database in SSMS

🚂 The next chapter brought the schema to reality in SSMS. I wrote CREATE TABLE statements to define the Flights, Airports, and Airlines tables, incorporating constraints like NOT NULL for critical fields (e.g., flight numbers). I extracted data from the BTS filtered table, uploading it using SSMS import tools for the Flights table and entering data row by row for Airports and Airlines, carefully mapping columns to fields (e.g., flight date to DATETIME). Validation queries like SELECT COUNT(*) (~30,000 flight records) and SELECT TOP 10 * confirmed data accuracy, ensuring a reliable database ready to fuel analysis. 🛠️✔️😊

🧑‍💻 Uncovering Insights with SQL

🌍 The heart of the story was querying the data to reveal MCO’s operational insights. In SSMS, I filtered the Flights table to focus solely on MCO arrivals, using conditions to isolate relevant flights. I organized queries into four analytical phases, stored in folders (stage1_exploratory/, etc.):

Exploratory Analysis: Used GROUP BY and COUNT to identify peak days (Dec 21 & 28, Sundays, 2,327 flights) and top cities (New York: 1,200 flights, Atlanta: 1,000). 📅
Operational Performance: Applied CASE and AVG to assess airline reliability (Delta: 85% on-time, JetBlue: 60%). 🕒
Route Analysis: Leveraged INNER JOINs to connect MCO flights with cities and airlines for route insights. 🛤️
Trend Analysis: Used RANK and SUM OVER to detect cancellation spikes (on Dec 28). 📊

Practicing CTEs and partitioned aggregations honed my skills, while the queries illuminated strategies like staffing needs, making the data actionable for MCO. 📉🌟

🎨 Bringing Data to Life with Tableau

🪄 To make the insights shine, I turned to Tableau, crafting interactive visualizations from query outputs. A bubble chart highlighted Sundays as the busiest days (2,327 flights), a line/bar chart tracked daily flights and cancellations (peak on Dec 28), a treemap showcased top cities (New York, Atlanta), and a table detailed airline performance (Delta’s reliability). These visuals transformed complex data into clear, engaging displays, making trends accessible for MCO’s decision-makers. 🫧📊✨

🖌️ Sharing the Story with a Canva Report

🌺 The final act was presenting my findings in a professional report crafted in Canva. The report opened with an introduction framing the project’s goals and MCO’s tourism context, followed by visual sections featuring Tableau charts (e.g., bubble chart, treemap). Findings summarized key insights (e.g., 28th cancellation spike, Delta’s 85% on-time rate), and recommendations offered actionable steps (e.g., extra staffing, Disney/Universal partnerships). Using Canva’s templates, I created a vibrant, organized layout with clear headings and colors, ensuring the report was engaging and easy for MCO authorities to act on, highlighting my ability to communicate effectively. 📝🖼️✨

🌟 Impact and Skills Demonstrated

🎊 This project weaves a story of transforming raw data into impactful insights for MCO’s holiday operations. With humility, I share the skills I applied:

📂 Data Extraction: Filtered and extracted BTS data.
🏗️ Schema Design: Built a relational schema.
💻 Database Setup: Created and populated SSMS tables.
🧑‍💻 SQL Querying: Developed targeted queries.
🎨 Visualization: Created Tableau dashboards.
📝 Reporting: Designed a Canva report.

I’m passionate about crafting data-driven solutions and eager to contribute to innovative teams! 🎉😊

🤝 Let’s Connect!

🎈 Ready to explore my work or talk data analytics? I’d love to connect! Dive into my code or reach out to spark ideas for driving impact with data. Let’s create data magic together! 🚀✨

Link: