data-analysis-portfolio
Paolo Vasta’s Data analysis portfolio
I am a data analyst with an engineering and B2B product marketing background.
My past professional and educational experience in multinational companies shapes how I frame questions, interpret results, and communicate actionable insights to non-technical stakeholders.
I focus on extracting practical value from real-world data using Python, SQL, and Power BI.
🔬 Interests, Tools & Technlogies
Primary focus:
- ETL
- Data analysis with Python (pandas, numpy, matplotlib) and SQL (PostgreSQL & T-SQL)
- Business analysis and visualization with Excel and Power BI
- Structured problem-solving applied to real-world datasets
Supporting tools and environments:
- SQL (foundations & data handling; Microsoft SQL Server)
- Swift & Xcode (iOS prototyping), Visual Studio (Python scripting)
- GitHub, Jira
- macOS, Linux, Windows
📊 Featured Projects
Goal: Evaluate real-world fuel consumption data to determine whether hybrid ownership delivers measurable cost savings and to identify the most efficient commuting route.
Key insight: Hybrid usage reduced fuel costs by approximately 15% on average, with consistent savings across different commuting routes.
Tools: Excel, Power BI
Explore:
- Power BI Desktop file
- Sample visualization:
Goal:
Build a proof-of-concept analytics pipeline to visualize multi-store sales performance and customer buying behavior while ensuring PII is removed at ingestion and never exposed in BI tools.
What I focused on:
Privacy-by-design ETL, analytical reasoning (fixed markup → profit ≈ revenue), scalable pipeline design, and effective dashboards.
Tools:
Python (ingestion, parsing, anonymization), Power BI (visualization)
Explore:
- Python data ingestion & anonymization pipeline:
👉 Privacy-First Sales Analytics Pilot (Car Dealership) (Python) - Power BI dashboard (local pilot):
👉 Privacy-First Sales Analytics Pilot (Car Dealership) (Power BI)
Swift-based prototype for estimating EV charging costs and comparing efficiency metrics using user-input and consumption data.
💡 Focus Areas & Analytical Edge
- Engineering-led data analysis focused on efficiency, cost, and performance trade-offs
- Product-oriented mindset: framing analytical questions around decisions, not just metrics
- Strong experience working with longitudinal, real-world datasets
- Clear communication of insights for non-technical stakeholders
📫 Contact
I am open to data analyst and analytics roles, particularly where technology and business insight intersect.
🪪 License
© 2026 Paolo Vasta. All rights reserved.
The content of this repository is made publicly available for viewing and educational reference only.
No reuse, modification, or redistribution of any part of this repository is permitted without explicit written permission from the author.