About Me
I’m Daniel Toluwani Adeleke, a Data Scientist dedicated to transforming complex datasets into meaningful, strategic insights. With an MSc in Data Science & Business Analytics and a BSc in Computer Science, I bring a strong academic foundation and practical experience in predictive modeling, data engineering, and business intelligence. I specialize in building data-driven solutions using Python, SQL, and machine learning, with a focus on solving real-world problems and driving smarter decision-making for businesses.
Data Warehouse & Analytics Project
This project demonstrates the design and implementation of a full-scale data warehousing solution using the Medallion Architecture framework. It includes ETL processes, data modeling, and analytics with SQL Server.
Tech stack: SQL Server ETL Power BI
Heart Disease Diagnosis using Machine Learning
Developed during my MSc dissertation, this project predicts heart disease using supervised ML models including Random Forest, Decision Tree, and SVM. Includes a Tkinter GUI for predictions.
Tech stack: Python Scikit-learn Tkinter
Restaurant Delivery Service Database Project
A local food delivery company migrated from CSV-based storage to a structured SQLite database with a GUI built using Tkinter. This project involved data migration, database design, and Python scripting.
Tech stack: SQLite Python Tkinter
