Category: SQL
Tools: PostgreSQL · pgAdmin · SQL
Data analysis project using PostgreSQL on two global datasets: World Data 2023 (socioeconomic indicators by country) and Global Energy (worldwide energy production and consumption). The goal is to answer concrete questions through 11 structured queries organized in three thematic groups.
| Group | Focus | Queries |
|---|---|---|
| A | Filtering and sorting | 5 queries |
| B | Aggregations and statistics | 3 queries |
| C | JOIN between the two datasets | 3 queries |
- Which countries have high GDP but low life expectancy?
- Is there a correlation between renewable energy and human development?
- What are the geographic distributions and outliers in energy consumption?
global-data-analysis/
├── SCRIPT_SQL.sql # All 11 queries
├── Progetto SQL di Francesco Benassi.pdf # Full project report
├── dataset/
│ ├── world-data-2023-clean.csv # Cleaned socioeconomic dataset
│ └── global-energy-clean.csv # Cleaned energy dataset
└── query-results/
├── Query_A1.png – Query_A5.png # Group A results
├── Query_B1.png – Query_B3.png # Group B results
└── Query_C1.png – Query_C3.png # Group C results
Project developed as part of the Master's program in AI & AI Agents for Business – Start2Impact × UniMarconi