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An end-to-end data pipeline which extracts divvy bikeshare data from web loads it into data lake and datawarehouse transforms it using dbt and finally , a dashboard to visualize the data using looker studio, the pipeline is orchestrated using prefect
🛸 This project showcases an Extract, Load, Transform (ELT) pipeline built with Python, Apache Spark, Delta Lake, and Docker. The objective of the project is to scrape UFO sighting data from NUFORC and process it through the Medallion architecture to create a star schema in the Gold layer that is ready for analysis.
Builded an ETL pipeline using Python, Pandas, Python dictionary methods and regular expressions to ETL data. It involves extracting data from multiple sources, cleaning and transforming the data using Jupyter Notebook with pandas, numpy, and datetime packages, and loading the cleaned data into a relational database using pgAdmin
An ELT pipeline built for the pNEUMA open dataset of naturalistic trajectories of half a million vehicles collected by a swarm of drones in a congested downtown area of Athens, Greece.
This is an ELT data pipeline setup to track the activities of an e-commerce website based on orders, reviews, deliveries and shipment date. This project utilized technologies like Airflow, AWS RDS-Postgres, Python etc.