Data Analytics Portfolio
Welcome to my data analytics portfolio!
This repository contains projects I’ve worked on to showcase my skills in data analysis, visualization, and storytelling amoung others.
🤗 About Me
Hi, I’m Marta 👋
I’m a data analyst with a background in customer success and technical managment and onboarding of B2B customers. I don’t just crunch numbers, I know how to translate insights into actions that teams actually use. Over the last few years, I’ve built dashboards and models in Power BI, Looker, Excel and Zendesk Explore, making complex data accessible to executives, product managers, and support teams.
What sets me apart is that I’ve worked on both sides of the table: leading large technical and customer-facing teams and later shifting into analytics. That means I bring not only the technical skills (SQL, Python, BI tools) but also the ability to communicate findings, train teams, and drive adoption.
I love tackling messy datasets, finding patterns, and presenting them in a way that sparks “aha!” moments. Right now, I’m expanding my skills through hands-on projects in Python and machine learning, with the goal of growing, one day, into a data scientist role.
📊 Specialties: turning raw data into actionable insights, dashboard storytelling, customer behavior analysis, and cross-team collaboration.
🌍 Based in Oslo, originally from Barcelona.
⚡ Fun fact: I grew up around books, studied philosophy and literature, and now apply that same curiosity to data.
📂 Projects in this Portfolio
1. Insurance Costs Analysis
- Description: Analysis of the “Medical Insurance Costs” dataset.
- Skills Used: Python, Pandas, Matplotlib, Seaborn
- Highlights: Investigated relationships between BMI, smoking, and insurance charges.
- README: Introduction to the project
- Notebook: insurance_analysis.html
2. Rating Red Vinho Verde
- Description: Predictive analysis of Portuguese red Vinho Verde wines, identifying key chemical properties that drive quality and building models to support restaurant managers in selecting high-quality wines.
- Skills Used: Excel, Data visualization, Logistic Regression, Segmented Regression, Polynomial Regression, Multinomial Regression, OvR, Python, PowerPoint, Gimp
- Highlights:
- Multinomial logistic regression achieved high accuracy in predicting wine quality.
- Sulphates and Alcohol were the most significant chemical predictors.
- Provided actionable insights for managers on evaluating and selecting wines.
- The presentation summarizes insights in a clear, accessible way for both technical and non-technical stakeholders to support data-driven decisions.
- README: Introduction to the project
- Report: Project report.pdf
- Power Point Presentation: Presentation.pdf
3. NBA Trends
- Description: Analysis of the ‘NBA games” dataset.
- Skills Used: Python, Pandas, Numpy, Matplotlib, Seaborn, Scipy
- Highlights: Explore NBA game data to compare the performance of the New York Knicks and the Brooklyn Nets in the 2010 and 2014 seasons.
- README: Introduction to the project
- Notebook: nba_thrends.html
4. (Future Project)
Coming soon 🚀
- Python (Pandas, Matplotlib, Seaborn, Scipy, Numpy)
- SQL (MySQL)
- Excel (Power Query, Power Pivot, advanced formulas, regression & statistical analysis, forecasting, interactive dashboards)
- Data Visualization (Power BI, Looker, Excel, Zendesk Explore)
- Statistical Analysis & Data Cleaning
🌐 Portfolio Website
You can also view this portfolio as a website here:
👉 Data Analytics Portfolio - WIP 🚧