Welcome,I’m a data analyst with a background in nursing, passionate about turning health and human-centered data into actionable insights.
##About Me I specialize in data cleaning, visualization, and reporting using Excel, SQL, and Power Bi## Projects
Description:- Analyzed real-world datasets across variables like employment, marital status, education, alcohol use, diet, and chronic illnesses. Tools Used: Excel, Power BI Key Findings:
![Dashboard Lifestyle and Health prediction Analysis ])(
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Description: - Cleaned and structured sales data from a fashion brand to identify best-selling product categories and seasonal performance
Tools Used: Excel, Power BI
Key Findings:
Description:-It presents an analysis of 100 applicants from the DAWB Data Analytics Training (Cohort 2), highlighting key insights from application sources, employment status, selection process, and geographic reach.
Tools Used: Excel, Key Findings:
-📊 Application Process: Out of 100 applicants, only 23 advanced to selection, showing DAWB’s strong emphasis on quality and readiness.
-🧭 Application Source: Referrals brought in the highest number of applicants, followed by social media. The DAWB community believes in and promotes the program — that’s true impact!
-💻 Employment Status: Most applicants are employed professionals, reflecting a growing interest in using data skills to enhance career growth.
-🌍 Geographic Spread: Lagos and the Southwest region dominate participation, showing DAWB’s strong regional influence and room to reach other zones.
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Description:-This project analyzes workplace burnout using a multi-dimensional dataset covering work hours, sleep duration, physical activity, years of experience, gender, and productivity metrics. I designed a comprehensive dashboard visualization to communicate patterns and risk factors contributing to employee burnout.
Tools Used: Excel Key Findings:
-Those working between 40–49 hours per week reported the highest burnout levels. It wasn’t the people working the longest hours — it was those in the “almost too busy” range. Sometimes, burnout doesn’t happen at the extreme; it creeps in when you think you’re still managing fine.
-There was only a small difference between male and female employees, but men showed slightly higher burnout levels. It’s a reminder that burnout has no respect for gender — it affects anyone, no matter how strong or composed they appear.
-People who get more sleep have higher productivity — rest isn’t a luxury; it’s an efficiency tool.
-Employees with the longest years of service had the highest burnout levels — loyalty shouldn’t lead to depletion.
-Those who engage in more physical activity report lower stress — small steps literally make a big difference.
-The more burnout increases, the less satisfied people feel with their jobs — when well-being declines, so does engagement. View Project Files →)
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