A portable Datamart and Business Intelligence suite built with Docker, Mage, dbt, DuckDB and Superset
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Updated
Nov 9, 2024 - Dockerfile
A portable Datamart and Business Intelligence suite built with Docker, Mage, dbt, DuckDB and Superset
This end-to-end data pipeline project 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.
In this project, I demonstrate creating a data pipeline from NYC Taxi data using Mage.ai for ETL, GCP for storage and BigQuery, and Looker Studio for analytics.
Project 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.
mlops zoomcamp capstone project
Personal project for Data Engineering Zoomcamp
Data Engineering Zoomcamp 2024
A data engineering project built around Smogon's Stats API.
Data Engineering on GCP and Mage AI
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.
Data Engineering Pipeline for Uber Data Analysis using Google Cloud Platform, Mage-AI and Looker
Solutions for @DataTalksClub's Data Engineering Zoomcamp 2024.
Developed an interactive dashboard utilizing Google Looker Studio to analyze Uber usage patterns in NYC. Designed a robust data model and implemented an efficient data pipeline using Mage AI on GCP's VM infrastructure. Utilized Google BigQuery for in-depth analytics and leveraged Google Cloud Platform for data processing.
An end to end Data Engineering Project
Engineered a robust data pipeline using Google Cloud Platform (GCP) services like Cloud Storage, Compute Engine, BigQuery, resulting in a 30% decrease in data processing and analysis time of the San Francisco Crime dataset.Designed an interactive dashboard using Looker Studio, empowering stakeholders to explore crime data visually.
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