I am a data professional focused on transforming raw data into clear insights that support better business decisions. My work combines data analytics, business intelligence, machine learning, and data visualization to solve practical business and research problems.

I enjoy working across the complete analytics workflow — from data preparation and modelling to analysis, dashboard development, machine learning, and communicating findings to decision-makers.

Data Analytics & Business Intelligence

• Power BI
• Microsoft Excel
• Power Query
• DAX
• Data Modelling
• KPI Development
• Dashboard Design
• Business Intelligence

Programming & Databases

• Python
• SQL
• Microsoft SQL Server

Data Science & Machine Learning

• Pandas
• NumPy
• Scikit-learn
• XGBoost
• Machine Learning
• Predictive Modelling
• Time-Series Analysis
• Model Evaluation

Analytics Areas

• Sales Analytics
• Customer Analytics
• Product Performance Analysis
• Geographic Analysis
• Business Performance Analysis
• Public Health Data Analytics
• Hr Analytics
• Health Analytics

A leakage-aware machine learning project developed to forecast weekly Lassa fever cases using temporal surveillance data.

The project applies time-aware feature engineering and machine learning techniques to analyse disease trends while avoiding temporal data leakage.

• Time-series feature engineering
• Lag and rolling features
• Machine learning regression
• Temporal validation
• Model performance evaluation
• Public health forecasting

Python Pandas Scikit-learn XGBoost Machine Learning

🔗 View Project

An interactive Microsoft Excel HR analytics project developed to examine employee turnover and identify workforce segments with higher attrition risk.

The project analyzes 1,470 employees across demographics, job roles, departments, age groups, business travel, job satisfaction, performance, and other workforce factors.

• 1,470 total employees
• 237 employee attritions
• 16% overall attrition rate
• 1,233 active employees
• 84% active employee rate
• 34 years average age of employees who left
• Analysis by gender, age group, department, job role, education field, and business travel
• Interactive HR dashboard with slicers and KPI indicators

Microsoft Excel Power Query PivotTables PivotCharts Slicers Data Cleaning HR Analytics Dashboard Design

🔗 View HR Employee Attrition Analytics Project

An interactive Power BI business intelligence solution developed to analyse sales performance across customers, products, sales teams, transactions, time periods, and geographic locations.

• Revenue and profitability
• Customer retargeting
• Product performance
• Sales team performance
• Shipping and delivery performance
• Sales channel performance
• Time-based sales trends
• Regional and location analysis

Power BI DAX Power Query Data Modelling Business Intelligence

🔗 View Project

A classical time-series forecasting project developed in Microsoft Excel to analyze quarterly car sales, identify seasonal patterns, estimate the underlying sales trend, and forecast sales for Year 5.

The project applies moving averages, centered moving averages, seasonal decomposition, deseasonalization, simple linear regression, and re-seasonalized forecasting.

• 16 historical quarterly observations across four years
• 4-quarter moving average and centered moving average
• Quarterly seasonal index calculation
• Deseasonalized sales analysis
• Linear trend modelling using regression
• R² = 0.921
• Year 5 quarterly sales forecasting
• Total Year 5 forecast of approximately 31.40 ('000)
• Q4 identified as the strongest seasonal quarter
• Q2 identified as the weakest seasonal quarter

Microsoft Excel Time Series Analysis Moving Average Centered Moving Average Seasonal Decomposition Deseasonalization Linear Regression Forecasting Data Visualization

🔗 View Quarterly Sales Time Series Forecasting Project

An interactive Microsoft Excel healthcare analytics project developed to analyze patient admissions, diagnoses, demographics, hospital activity, regional patterns, and length of stay.

The project transforms healthcare admission records into an interactive decision-support dashboard for understanding patient demand and hospital performance.

• 100 patient admissions analyzed
• 6 hospitals
• 6 diagnosis categories
• 5 geographic regions
• 51.8 years average patient age
• 7.6 days average length of stay
• Hospital, diagnosis, region, and gender filtering
• Automated filter reset using VBA
• Analysis of monthly admission trends and patient age groups

Microsoft Excel Power Query PivotTables PivotCharts VBA Slicers Healthcare Analytics Data Visualization

🔗 View Healthcare Admissions Analytics Project

I am particularly interested in using data to answer practical questions such as:

• What is driving business performance?
• Which customers, products, or locations require attention?
• How can historical data support forecasting and planning?
• How can complex datasets be presented clearly to decision-makers?
• How can machine learning improve prediction without compromising analytical reliability?

• Building end-to-end data analytics portfolio projects
• Developing interactive business intelligence dashboards
• Applying SQL and Python to real-world analytical problems
• Building machine learning and forecasting solutions
• Improving data storytelling and decision-support systems

This GitHub profile contains projects demonstrating practical experience in:

Power BI • SQL • Python • Excel • Machine Learning • Data Visualization • Business Intelligence • Data Science

More projects will be added as the portfolio continues to grow.