📊 Aspiring Data & Business Intelligence Analyst • 🎓 Information Systems Graduate • 🧠 Logical Problem Solver
I am a recent BCom Information Systems graduate from North-West University with a passion for turning "messy" data into clear, actionable business insights. I’m focused on building a career where I can bridge the gap between technical data and business needs.
I enjoy the challenge of finding patterns in data and using those findings to help businesses make better decisions. I also actively use Generative AI (ChatGPT, Google Gemini) to speed up my coding, improve my project documentation, and learn new analytical techniques faster.
This GitHub profile is a collection of my hands-on projects, showing how I handle data from start to finish, from data cleaning and SQL modeling to statistical analysis and BI dashboarding that tell a story.
- Exploratory Data Analysis (EDA): Digging into datasets to find trends, risks, and opportunities.
- Visual Storytelling: Creating dashboards that make complex numbers easy for anyone to understand.
- KPI Focused: Understanding that data is only useful if it helps measure and achieve business goals.
- Problem-to-Data Translation: Taking a business question and figuring out exactly what data is needed to answer it.
- Requirements Gathering: Working to understand what stakeholders actually need from a report or tool.
- Logical Thinking: Ensuring data models follow clear business rules and provide accurate results.
- Statistical Inference: Applying hypothesis testing, p-values, and confidence intervals to validate findings.
- Probability & Risk: Using probability distributions to model business uncertainty and risks.
- Linear Algebra & Calculus: Leveraging mathematical foundations for data transformation, optimization, and understanding machine learning logic.
- Data Cleaning: Using Python and SQL to fix inconsistencies and prepare datasets for analysis.
- SQL Queries: Comfortable writing joins, aggregations, and subqueries to pull the right information.
- Python: Pandas, NumPy, Matplotlib, Seaborn (For analysis and visualization).
- SQL: MySQL / PostgreSQL (Relational modeling and analytical queries).
- Excel: Advanced formulas, Pivot Tables, and Power Query.
- GenAI Tools: Using ChatGPT and Gemini for prompt engineering, debugging code, and drafting clear reports.
- BI Tools: Tableau & Oracle Analytics Cloud (Designing interactive dashboards).
- Workflow: Git/GitHub, Jupyter Notebooks, and VS Code.
When I tackle a project, I follow a simple, logical process:
- Define the Goal: What business question am I trying to answer?
- Get & Clean Data: Pulling data with SQL and cleaning it with Python/Excel.
- Validate: Apply Statistical Inference to ensure data integrity and significance.
- Analyze: Finding the "why" behind the numbers.
- Enhance with AI: Using AI to double-check my logic, optimize my code, and document my work.
- Visualize: Building a dashboard or report that shows the solution clearly.
I’m looking for opportunities to grow and contribute as a:
- Junior Data Analyst
- Business Intelligence Analyst
- Junior Business Analyst
💡 “Data creates insight. AI accelerates understanding. Decisions create value.”
Learning every day. Building one project at a time.