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Hi, I'm Vincenzo Di Sario 👋

📊 Data Analyst | SQL · Python · Tableau · Power BI

Data Analyst with expertise in SQL data modeling, ETL workflows, and dashboard development. I specialize in transforming complex datasets into actionable business insights, with a focus on customer analytics, retention patterns, and performance reporting. Based in Barcelona, I build end-to-end analytics pipelines that bridge the gap between raw data and strategic decision-making.

Additionally, I conduct financial analysis training for FAO, helping professionals strengthen their ability to interpret project KPIs and assess business-plan viability.


🛠️ Technical Skills

Data & Analytics:
SQL (SQL Server, PostreSQL, MySQL) · Python (Pandas) · Excel (Power Query, Pivot Tables, Data Modeling)

Business Intelligence:
Power BI (DAX, Data Modeling) · Tableau (LOD Expressions, Interactive Dashboards)

Data Engineering:
ETL Pipelines · Data Cleaning & Transformation · SQL Views & CTEs


💼 Professional Portfolio Projects

Excel · Python · SQL Server · Power BI · Tableau

Complete analytics workflow transforming 4,184 messy delivery orders into strategic business recommendations with €50K+ in identified growth opportunities.

What I Built:

  • Data Cleaning Pipeline - Anonymized 1,805 customers, parsed unstructured product text using Python regex, standardized 24 months of delivery data
  • SQL Analytics Layer - Built customer retention KPIs, churn cascade analysis, promotional ROI metrics using window functions and CTEs
  • Dual Dashboard Strategy - Power BI for insight storytelling (retention crisis, discount inefficiencies), Tableau for self-service exploration

Key Skills: Data Quality Assessment, Customer Segmentation, Retention Analysis, KPI Design, Financial Modeling, Data Storytelling

📂 View Project | 📊 Live Tableau Dashboard


📚 Learning & Practice Projects

SQL Server · ETL Pipelines · Star Schema Modeling

Built a complete data warehouse from scratch using the Medallion Architecture (Bronze, Silver, Gold layers) to understand the upstream data engineering processes that enable analytics work.

What I Built:

  • Bronze Layer (Raw Ingestion) - Implemented full-load ETL with BULK INSERT, error handling (TRY/CATCH), and performance measurement
  • Silver Layer (Data Quality) - Applied deduplication (ROW_NUMBER()), standardization (CASE WHEN), null handling, date enrichment (LEAD()), and business rule validation
  • Gold Layer (Star Schema) - Created fact and dimension tables with surrogate keys, integrated multi-source data (ERP + CRM), built analyst-friendly views

Why This Project:

As a data analyst, I realized I had a critical knowledge gap: I didn't understand how data arrived in its analysis-ready state. By building this warehouse myself, I learned:

  • Data Lineage: How to trace transformations from source to final model
  • Data Quality Patterns: Why duplicates, nulls, and inconsistencies occur and how to fix them at the source
  • Modeling Decisions: Why star schemas use surrogate keys and how integration rules work
  • Engineer Collaboration: How to speak the technical language of ETL pipelines and data integration

Key Skills: ETL Development, Data Quality Management, Star Schema Design, Window Functions, Stored Procedures, Data Integration

📂 View Project

Built following the excellent tutorial by Data With Baraa - implemented hands-on to deepen understanding of data engineering fundamentals.


📚 Currently Learning

I'm continuously expanding my technical toolkit with:

🐍 Advanced Python for Data Analysis

  • Pandas, Numpy
  • Data visualization with Matplotlib & Seaborn
  • Working with APIs for data extraction

☁️ Azure Cloud Computing

  • Azure Data Factory for ETL orchestration
  • Azure SQL Database management
  • Cloud-based analytics architecture

🔧 Data Engineering in SQL

  • Performance optimization and query tuning
  • Stored procedures and functions
  • Advanced data modeling patterns

📊 Additional Focus Areas

  • Statistical analysis and hypothesis testing

Languages:

  • Italian (Native)
  • English (Professional Working Proficiency)
  • Spanish (Professional Working Proficiency)
  • French (Professional Working Proficiency)

📧 Let's Connect

I'm open to Data Analyst and Business Intelligence Analyst opportunities where I can:

  • Build scalable analytics pipelines and dashboards
  • Translate business questions into data-driven insights
  • Collaborate with cross-functional teams on strategic initiatives
  • Drive measurable business impact through analytics

Location Preference: Barcelona (hybrid/remote) or Remote (Europe)

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📄 Resume / CV

For a complete overview of my experience and qualifications:

Download CV

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Last Updated: December 2025

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