Apcondessa

Hi, I’m Ana Condessa 👋

Data Analytics | Business Intelligence | Data-Driven Decision Making

I’m a business-oriented data professional with experience in customer success, project management, and performance analysis, currently specializing in Data Analytics and Business Intelligence through FIAP’s Data Analytics postgraduate program.

I combine business understanding with hands-on experience in data analysis, visualization, and cloud-based data processing to transform raw data into actionable insights that support better decisions.

📍 Belo Horizonte, Brazil

Open to remote and international opportunities

🛠️ Technical Skills

Data Analysis & Programming

Python, Pandas, NumPy
SQL, Spark SQL
Exploratory Data Analysis (EDA)
Data cleaning, validation, and transformation

Business Intelligence & Visualization

Power BI, DAX
Excel
Matplotlib
KPI development, dashboard design, and analytical reporting

Big Data & Cloud

Amazon S3
AWS Glue
Amazon Athena
PySpark
Data Lake architecture (Bronze, Silver, and Gold layers)

Machine Learning

Scikit-learn
Classification models
Feature engineering and model evaluation

Tools & Foundations

Jupyter Notebook
Git and GitHub
HTML5 and CSS3 fundamentals

🚀 Featured Projects

1. The Data & AI Market in Brazil

**FIAP Tech Challenge

Big Data Analytics**

An end-to-end data project exploring Brazil’s data and AI job market using industry survey data.

Built a cloud-based Data Lake with Bronze, Silver, and Gold layers.
Worked with Amazon S3, AWS Glue, PySpark, Spark SQL, and Amazon Athena.
Applied data transformation and exploratory analysis to support business-oriented insights.

🔗 View Project on GitHub

2. E-commerce Analytics — Olist

**FIAP Tech Challenge

Business Intelligence**

An analytical project focused on e-commerce performance, sales, and customer behavior.

Analyzed sales, freight, delivery performance, and repeat purchases.
Developed KPIs to evaluate revenue, customer retention, and regional performance.
Used Python and Power BI to support data-driven business recommendations.

3. Wine Quality Classification

**Machine Learning

Python

Scikit-learn**

A machine learning project focused on predicting wine quality using classification techniques.

Performed exploratory data analysis and feature engineering.
Compared classification approaches and evaluated model performance.
Achieved 85.42% accuracy with Random Forest in the project evaluation.

🔎 Explore my repositories

📊 Core Competencies

Translating business questions into analytical problems
Data cleaning, exploration, and quality validation
KPI definition and performance monitoring
Dashboard development and data storytelling
Customer behavior and business performance analysis
Structured problem-solving and cross-functional collaboration

🎯 Current Focus

Advancing my skills in Data Analytics and Business Intelligence
Building end-to-end analytics and Big Data projects
Strengthening SQL, Python, Power BI, and cloud data processing
Connecting data pipelines, analytical insights, and business decisions

🎓 Postgraduate Program in Data Analytics — FIAP

🤝 Let’s Connect

I’m interested in opportunities where data, technology, and business strategy come together to solve real-world problems.