Insights, tutorials, and thoughts on data engineering, analytics, and technology
A deep dive into building ChessLens, an end-to-end chess analytics platform using dbt, DuckDB, Dagster, and Streamlit. Covers tilt detection, session analysis, opening trends, and on-demand Stockfish evaluation — turning 1,379 chess.com games into actionable insights about when, how, and why I lose.
In this article, I share my journey building a data pipeline for Formula 1 racing data using modern technologies. Learn how I leveraged PostgreSQL for storage, Kafka and Debezium for streaming, and DuckDB with dbt for analytics, implementing advanced patterns like CDC and SCD Type 2 along the way.
This tutorial explains how to build a content-based filtering system that predicts user ratings for movies based on their preferences. Learn the fundamentals of recommendation systems, from data preparation to similarity calculation and prediction, with practical Python implementation.
In this article, I detail how I built the data collection layer for my F1 pipeline using Python-based collectors with async programming, robust error handling, and efficient connection pooling. I explain the challenges of collecting Formula 1 data and share lessons learned from implementing API integration and web scraping solutions.