Video Game Sales Analysis
I analyzed global sales data to uncover platform and genre trends, and created interactive visualizations to compare regions.
Hüseyin Can Akkaya
I'm
Data Analyst with a passion for exploring data, visualizing trends, and delivering clear, actionable reports that empower organizations to make better decisions.
About Me
My introduction
Hi, I’m Hüseyin Can Akkaya. I enjoy turning raw data into meaningful insights that support better decision-making. My journey started with curiosity about how data can reveal patterns and trends, and today I use tools like Python, SQL, and Power BI to analyze, visualize, and report on data. While my current focus is on data analysis and business intelligence, my future goal is to expand my expertise into web development and create digital platforms that bring together data and technology.
Data Analysis
Python
Pandas
NumPy
Scikit-learn
Matplotlib
Seaborn
Plotly
MSSQL
Excel
PowerBI
Tableau
Projects
Selected work in Data Analysis & BI
House Prices: Regression
I predicted house prices through missing value handling, log transformations, and modeling; feature engineering and error metrics were reported.
E-Commerce Sales Analysis
End-to-end analysis of an e-commerce sales dataset using MSSQL and Python, including data cleaning, ETL, analysis, and customer segmentation (RFM).
Covid-19 Analysis with Tableau and SQL
In this project, Covid-19 case and death data were processed using SQL to extract meaningful insights. Interactive visualizations were then created with Tableau to present case trends, death rates, and comparisons across countries and continents. The project covers end-to-end steps of data cleaning, querying, and visualization.
Pusula – Hüseyin Can Akkaya
This repository contains exploratory data analysis (EDA) and feature engineering on a Physical Medicine and Rehabilitation dataset as part of the Pusula project. The work focuses on the target variable TreatmentDuration, including data cleaning, transformations, visualizations, and correlation analysis.
NashvilleHousing – SQL Data Cleaning
This project involves a data cleaning process carried out on the NashvilleHousing dataset using SQL. In this study, date formats were standardized, missing address data was completed based on records with the same parcel, property and owner information was separated into individual columns, inconsistent values in the SoldAsVacant field (Y/N) were standardized as Yes/No, duplicate records were identified and prepared for cleaning, and unused columns were removed from the table for simplification. As a result, the dataset has become more consistent, analyzable, and ready for reporting.
Movie Analysis - Correlation in Python
This project performs cleaning, exploratory data analysis (EDA), and correlation analysis on the movie.csv dataset. The goal is to see the relationships between metrics such as budget, revenue, number of votes, and rating, and to gain fundamental insights.
Get in touch
Do you have a project in your mind, contact me hereFind me
Email: hcaakkaya@gmail.com