Adelakun Bukunmi

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View the Project on GitHub BukunmiAdelakun/portfolio

ABOUT ME

Hello! I’m Adelakun Bukunmi, a passionate data analyst and a medical doctor with a unique blend of clinical expertise and analytical skills. Alongside my medical practise, I developed a strong interest in data analysis. While my medical background has sharpened my problem solving abilities and attention to detail, my passion for data extends beyond healthcare, encompassing diverse industries and data types.

SKILLS

✔Data Cleaning and transformtion. I perform data cleaning, preprocessing, and transformation tasks to ensure data accuracy, consistency , and readiness for analysis.I handle missing values, outliers and data type conversions while restructuring datasets for optimal analytical performance.

✔Data Analysis. I apply stastical analysis using SQL, Microsoft Excel and Power BI to identify trends, patterns, correlations and key findings.

✔Data Visualization I present results of my aanalysis using clear charts, dashboards and reports. I also highlight key metrics, KPIs, and actionable insights.

✔Interpretation and Recommendation I translate my findings into clear, real world implications, provide suggestions and recommendations based on my analysis.

MY PROJECTS

✔CAR SALES ANALYSIS I carried out analysis on car pricing based on fuel type, gear typr and car condition over a particular period and found out how gear types, car conditions and car model affected car prices.

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✔HEALTH CARE ANALYSIS I generated actionable insights to highlight the prevalent medical conditions,insurance coverage disparities, admission trends over the years and was able to find out blood types assosciated with certain medical conditions.

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✔SOCIAL MEDIA ADICTION ANALYSIS I collected, cleaned, and analyzed data from 705 students to examine patterns of social media usage, addiction levels, and its effects on academic performance and sleep habits. Identified critical insights such as the most addictive platforms and how addiction levels varied across academic levels and gender.Provided data-driven recommendations for awareness campaigns and student support programs based on observed trends.

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