📊 Data Engineering and Analytics

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📌 A research area focused on structuring, processing, and analyzing large volumes of data.

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## 🧠 Key Topics

• Data warehouse architecture, ETL processes • Data modeling and normalization • Tools: SQL, Python, Power BI • Building data pipelines, stream processing • Visualization and interpretation of results • Integration with ML models and cloud platforms

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## 🛠️ Practical Cases

• Analytics dashboards for educational systems • Data architecture for university services • Implementing Apache Kafka, Airflow, Spark • Forecasting and classification models

📌 Supports case challenges, thesis projects, and interdepartmental research.