Hi, I'm Proud Ndlovu (GitHub: ApostolicDA) — a Data Analyst & Business Intelligence Specialist focused on transforming complex datasets into clear, actionable insights that support strategic decision-making.
My work centers around building data pipelines, analytical datasets, and executive dashboards that help organizations understand performance, identify opportunities, and make data-driven decisions.
I specialize in the full analytics lifecycle:
Raw Data → Data Cleaning → Data Modeling → Analysis → Executive Dashboards
🔹 Based in Johannesburg, South Africa
🔹 Experienced with SQL, Python, Power BI, and Looker Studio
🔹 Focused on business intelligence, analytics engineering, and KPI reporting
🔹 Passionate about turning messy operational data into reliable business insights
Capabilities
- Data cleaning and transformation
- SQL data modeling
- Exploratory Data Analysis (EDA)
- KPI development and validation
- Analytical dataset creation
- Business performance analysis
Capabilities
- Executive dashboards
- KPI reporting frameworks
- Business performance monitoring
- Funnel analysis
- Data storytelling for stakeholders
End-to-end analytics system integrating multiple admissions datasets into a PostgreSQL warehouse powering a validated BI dashboard.
Key Work
- Integrated 4 operational datasets into a governed analytical model
- Engineered a master dataset using SQL transformations
- Built a Looker Studio executive dashboard
- Implemented SQL-based KPI validation framework
Skills Demonstrated
SQL • Data Modeling • ETL • Data Governance • BI Dashboarding
🔗
Check Out My Governed-Admissions-Intelligence-Pipeline Project Here
SQL-driven analytics system designed to measure and optimize marketing return on ad spend (ROAS) across campaigns.
Key Work
- Built SQL queries calculating ROAS, CAC, LTV, churn risk, and channel profitability
- Developed multi-table analytical model using CTEs and window functions
- Created BI-ready datasets supporting executive performance monitoring
Skills Demonstrated
SQL • Marketing Analytics • KPI Modeling • Performance Analysis
🔗
Check Out My Roas Analytics Project Here
Exploratory analytics project investigating fraudulent transaction patterns using Python and SQL-based analysis.
Key Work
- Cleaned and validated financial transaction datasets
- Identified fraud rate (10.61%) and total financial exposure
- Performed segmentation analysis revealing fraud concentration patterns
Skills Demonstrated
Python • Data Cleaning • Exploratory Data Analysis • Risk Analytics
🔗
Check Out My Fraud Detection Project Here
| Capability | Business Value |
|---|---|
| Data Cleaning & Transformation | Ensures accurate and reliable datasets |
| SQL Analytics & Modeling | Converts raw operational data into structured analytical datasets |
| Dashboard Development | Enables executives to monitor KPIs and performance in real time |
| KPI Validation & Governance | Ensures dashboard metrics accurately reflect source data |
| Insight Generation | Translates complex data into actionable recommendations |
| Qualification | Institution | Year |
|---|---|---|
| Advanced Diploma – Data Science & Machine Learning | Alison | 2023–2025 |
| Data Analytics Bootcamp | aLex Data | 2025 |
| Microsoft Power BI Data Analyst (PL-300) | NEMISA | In Progress |
⭐ Goal: Build data systems and dashboards that help organizations move from raw data to confident decisions.