Apache Hive Hadoop Airline Analysis
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Updated
Jun 24, 2020
Apache Hive Hadoop Airline Analysis
This is a binary classification problem, The goal is to predict which of the two levels of satisfaction with the airline the passenger belongs to: Satisfaction, Neutral or dissatisfied
A Data Warehouse project analyzing 2022 U.S. domestic departures, delays, cancellations, and weather-related disruption patterns through ETL, dimensional modeling, and Tableau dashboards.
Power BI dashboard for analyzing 2015 airline cancellations and flight delays. Includes flight duration, delay and cancellation reasons, date, flight number, airline, airports, and scheduled/actual times. Visualizations show total flights, cancellations, delay reasons, and monthly trends.
Customer Segmentation in Airlines Using Unsupervised K-Means Modeling
End-to-end EDA on 300,153 Indian airline flight bookings | Analyzing price patterns across airlines, routes, departure times, booking windows & travel classes using Python, Pandas & Seaborn
AI-powered platform for intelligent operations in healthcare, pharma, and aviation.
Dual-domain AI framework for airline RM and digital analytics validation
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