Who Am I?
I'm a Computer Science 3rd year student who found his passion in taking his detective magnifying glass
and diving deep into the data, in order to uncover all the valuable insights it secretly holds.
That's why I've been on a journey to become a Data Analyst.
Honestly, I've always been too attentive to detail and I've always leaned to the analytical side of things,
so I see that Data Analytics is the best fit for me.
Being an ENFJ, just the thought that I can help businesses make crucial decisions is ultimately intriguing!
So, want to join me on this fun journey? Let's go!
📊 This project analyzes restaurant operations, orders, and customer data to identify top-selling menu items and customer preferences.
This project focuses on cleaning and preprocessing global layoff data, then analysis to uncover trends in company layoffs across industries and countries.
📊 This project focuses on cleaning and transforming Nashville housing data to improve data quality and usability for analysis.
This project explores COVID-19 data using MySQL to analyze global and country-specific trends, including infection rates, death rates, and vaccination progress.
This project demonstrates how to retrieve, clean, analyze, and visualize economic data using the FRED API (Federal Reserve Economic Data). Using Python, pandas, matplotlib, and plotly, this project explores economic trends through data visualization and statistical analysis.
This project analyzes Airbnb listings in Paris, focusing on data preparation, quality assurance, and visualization. The goal is to explore trends in listing prices, accommodations, and the impact of regulations over time using Pandas, Matplotlib, and Seaborn.
This project involves data cleaning, exploratory data analysis, and correlation analysis on a movies dataset.
This project focuses on cleaning and analyzing ultra-marathon race data, specifically for 50km and 50mi races in the USA from 2020. The goal is to prepare the dataset for meaningful insights and visualizations.
This project automates the process of retrieving cryptocurrency data from the CoinMarketCap API, performing data analysis & visualization using Python. The data is pulled at regular intervals, stored in a CSV file, and analyzed to gain insights into cryptocurrency price trends.
This interactive Tableau dashboard explores the Netflix catalog, providing insights into content distribution, top genres, ratings, and trends over time. The dashboard is dynamic, allowing users to filter and interact with the data.
This interactive dashboard provides insights into house sales in King County, Washington, using various filters and visualizations. It enables users to explore trends in house prices, distribution of key housing attributes, and relationships between view quality and condition ratings.
This Tableau dashboard analyzes British Airways customer reviews from March 2016 to October 2023. It provides dynamic insights into passenger experiences, ratings by different metrics, and trends over time.
This Sales Insights project, which takes the point of view of an imaginary Indian company aiming to understand why sales have been declining, in order to boost them, is an end-to-end data analysis pipeline, leveraging MySQL for Exploratory Data Analysis (EDA) and data cleaning, followed by Tableau for visualization. The project delivers dynamic dashboards to analyze revenue and profit trends across different markets, customer types, and product categories.
This project analyzes London's bike-sharing data using Python (Pandas) for data cleaning and exploratory data analysis (EDA) and Tableau for interactive visualizations.