A portable Datamart and Business Intelligence suite built with Docker, Mage, dbt, DuckDB and Superset
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Updated
Apr 5, 2026 - Dockerfile
A portable Datamart and Business Intelligence suite built with Docker, Mage, dbt, DuckDB and Superset
The Zoomcamp MLOps Course covers tools like MLflow, Mage, Flask, Prometheus, Evidently, Grafana, Prefect, Terraform, and GitHub Actions. It emphasizes experiment tracking, model deployment, monitoring, CI/CD, and orchestration, culminating in an end-to-end project integrating best practices in MLOps.
The CNPJ Data ETL Pipeline is designed to automate the download, processing, and storage of public CNPJ data from the Brazilian Federal Revenue. The pipeline is built with Mage.ai and AWS S3 to ensure efficient data management and scalability.
An end-to-end data engineering pipeline project that processes and analyzes Maintenance Work Orders using Mage, Docker, Google BigQuery, MariaDB, and Looker Studio. It features a seamless integration of cloud and open-source tools for scalable data storage, transformation, and visualization.
End-to-end data engineering project
Mage AI pipeline: scrape Amazon products & reviews with Bright Data APIs, analyze sentiment with Gemini AI, visualize on Streamlit. Docker setup.
An end to end Data Engineering Project
Data modeling and ETL pipeline for data analytics on Uber dataset using Google cloud storage, BigQuery, and Looker Studio
A data engineering project built around Smogon's Stats API.
An end-to-end data engineering project using Amazon S3, EC2, mage.io, Google BigQuery and Looker.
Solutions for @DataTalksClub's Data Engineering Zoomcamp 2024.
ETL pipeline that loads sensor data from parquet files into PostgreSQL. Built with Mage.ai for orchestration and Docker for containerization.
Docker image for Mage AI deployment using Docker
End-to-end Data Engineering pipeline analyzing tech job market trends using GCP, Terraform, Mage, and dbt. Correlates 1M+ rows of Stack Overflow developer interest with real-time job demand.
This project showcases a data engineering pipeline using Google Cloud Platform (GCP) for analyzing taxi trips data from New York City. The pipeline includes steps such as data collection, storage setup, ETL processing, database creation, and data visualization.
ETL workflow for stock data processing using Mage and PostgreSQL
A full data pipeline project. from the ETL to the Dashboard
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