flight_takeoff CASE STUDY

Aviation Sentiment | British Airways Insights

Architecting Data-Driven Operational Excellence through advanced sentiment analysis and fleet performance metrics.

Role

Business Analyst

Timeline

Feb - Mar 2025

Location

Liverpool, UK

Key Tool

Tableau

The Challenge

The primary objective was analyzing publicly available datasets on customer reviews, flight delays, baggage management, and sentiment analysis to derive actionable insights for a global carrier.

  • analytics Consolidating disparate sentiment data from various public forums.
  • speed Mapping flight delay correlations to baggage management efficiency.

Strategic Roadmap

A multi-phase approach ensuring data visualization adoption is seamlessly integrated into operational frameworks.

01
database

Ingestion & Cleaning

Aggregating public aviation datasets and normalizing sentiment scores for consistent benchmarking across fleet categories.

02
query_stats

Sentiment Modeling

Developing customized Tableau dashboards that bridge the gap between technical metrics and operational decision-making.

03
rocket_launch

Operational Sync

Deployment of real-time monitoring tools to stakeholders, ensuring immediate visibility into passenger satisfaction trends.

Technical Execution

Tableau Ecosystem

Advanced visual representations of complex aviation datasets, utilizing LOD expressions and parameter actions for deep-drill analysis.

DATA BLENDING FORECASTING DASHBOARD UX
hub

Complexity Map

Managing 50,000+ data points across 4 distinct operational silos.

12%

Efficiency Lift

Targeted through delay modeling.

verified_user

98% Data Integrity Rate

security

Ready for deep analysis?

Explore the complete technical breakdown and data methodology used in the British Airways project.