3-Month Internship Project – ExcelR Institute
High Cloud Airlines P1056
The objective of this project is to evaluate the operational and commercial performance of High Cloud Airlines by analyzing passenger transportation trends, flight volume distribution, and load factor efficiency. Using SQL-based data analytics, airline datasets are extracted, cleaned, transformed, and queried to generate accurate KPIs related to passenger volumes, booking patterns, flight performance, revenue generation, and route optimization. The analysis focuses on identifying high-performing carriers, top-demand and profitable routes, and seasonal travel patterns that influence business growth.
In addition, the project aims to design and implement a comprehensive Airlines Dashboard Analytics system using business intelligence and visualization tools to transform raw flight data—such as Total Flights, Total Passengers, and Load Factor—into actionable insights. Interactive dashboards visualize temporal passenger trends, compare carrier performance, and analyze route profitability to uncover opportunities for maximizing seat capacity, optimizing flight scheduling, improving fleet utilization, and enhancing overall operational efficiency and profitability. These insights support data-driven decision-making in airline route planning, resource allocation, and strategic business initiatives.
6-Month Internship Project – ExcelR Institute
STOCK MARKET ANALYSIS
The objective of this project is to analyze stock market data using Excel, SQL, Power BI, and Tableau to generate meaningful insights that support data-driven investment decisions. SQL is used to extract, clean, and transform historical stock price, volume, and financial data, while Excel is leveraged for exploratory analysis, KPI calculations, and trend evaluation. Power BI and Tableau are utilized to develop interactive dashboards that visualize market trends, price movements, returns, volatility, trading volume, and sector performance. The analysis focuses on identifying high-performing stocks, market patterns, and risk indicators through time-series analysis and comparative performance evaluation.
By integrating advanced visualizations, filters, and drill-down features, the dashboards enable investors and stakeholders to monitor portfolio performance, assess market volatility, and optimize investment strategies. This project demonstrates strong analytical, visualization, and business intelligence skills using industry-standard tools.
