Ronnal Esneyder Ortiz C. Agricultural Research Scientist | Data Analyst in Training
Research scientist with a Master's degree in animal production and 14 years of experience in agricultural research, experimental design, and statistical analysis. Currently expanding my toolkit into SQL, Python, and machine learning to bridge the gap between domain expertise and modern data science.
Background: Livestock production analytics · Spectral prediction models · Experimental data analysis
DataScience_Training/ │ ├── sqlTraining/ # SQL fundamentals → real-world analysis │ ├── exercises/ # Daily practice queries │ └── projects/ # Brazil E-commerce Analysis (Olist - coming soon) │ ├── PythonTraining/ # Python for data analysis (coming soon) │ ├── Projects/ # End-to-end data science projects │ ├── datasets/ # Datasets used across projects │ └── README.md # You are here
Status: 🟡 In Progress
Folder: sqlTraining/
Dataset: Brazilian E-Commerce by Olist
Analyzing 100K+ orders from a Brazilian marketplace to answer real business questions using SQL.
Business Questions Explored:
- ✅ How are delivered orders distributed across Brazilian states?
- ✅ Which states generate 1,000+ orders?
- ⬜ Revenue analysis by category
- ⬜ Delivery performance metrics
- ⬜ Customer segmentation patterns
SQL Skills Demonstrated:
SELECT · WHERE · GROUP BY · HAVING · ORDER BY · JOIN
· Aggregation Functions · Filtering
| Category | Tools |
|---|---|
| SQL | PostgreSQL, pgAdmin |
| Python | Pandas, Matplotlib (in progress) |
| Statistics | R, Experimental Design, ANOVA |
| Other | Git, GitHub, Kaggle Datasets |
| Phase | Focus | Status |
|---|---|---|
| 1 | SQL Fundamentals | 🟡 In Progress |
| 2 | SQL Real-World Project (Olist) | 🟡 In Progress |
| 3 | Python for Data Analysis | ⬜ Upcoming |
| 4 | Python + SQL Integration | ⬜ Upcoming |
| 5 | Agricultural Data Project | ⬜ Upcoming |
| 6 | Machine Learning Basics | ⬜ Upcoming |
With 14 years in agricultural research, I bring unique analytical perspective to data science:
- Livestock Production Analytics — performance metrics, feed efficiency, growth modeling
- Spectral Prediction Models — NIR/MIR spectroscopy for quality assessment
- Experimental Design — randomized trials, factorial designs, repeated measures
- GitHub: github.com/RonnalOrtiz
- LinkedIn: [www.linkedin.com/in/ronnalortiz-analisisdatos]
- Email: [reortizc@unal.edu.co]
"The goal is to turn domain expertise into data-driven solutions — one query at a time."