Data Scientist, Engineer, AI, Educator
This project is a hands-on implementation of a real-time algorithmic trading system that processes market data and news sentiment to make automated trading decisions. It integrates Apache Flink for stream processing, Redpanda for data streaming, and the Alpaca API for market data and trade execution, with sentiment analysis driving the strategy. Technologies Used How It …
This project involves the development of a real-time analytics dashboard designed to process and visualize voting data for an election simulation involving three political parties: Party A, Party B, and Party C. The system integrates multiple technologies to handle data streaming, processing, and visualization, demonstrating proficiency in modern data engineering tools. For a detailed overview, …
This project demonstrates the development of a real-time data pipeline for e-commerce sales analytics using Apache Kafka, Apache Flink, PostgreSQL, and Elasticsearch. The pipeline ingests high-throughput transaction data, processes it for real-time insights, and stores it for querying and visualization, addressing needs such as inventory optimization and fraud detection. For more details, refer to the …
In today’s data-driven world, real-time monitoring of database changes is critical for applications like fraud detection and live analytics dashboards. This project demonstrates a robust real-time data pipeline using PostgreSQL, Debezium, and Kafka, orchestrated with Docker, to capture and stream database changes efficiently. The project includes: Features Technology Used Learn More Link: Read the full …
This project is a real-time data pipeline that keeps tabs on YouTube video stats—like likes and views—using Kafka and ksqlDB. It pulls data from the YouTube Data API, processes it on the fly, and sends me a Telegram message when something noteworthy changes. How It Works Tech Stack Why It MattersIt’s a hands-on showcase of …