In this project, a thorough analysis of the βNew York City Airbnb Open Dataβ dataset was conducted using Python. The objective was to understand the fundamental characteristics of the data and extract meaningful insights.
Developed and implemented an end-to-end ETL pipeline for processinsg NYC Trip Record data. The pipeline encompassed extracting raw data, performing data transformation using Python, applying fact and dimensional data modelling techniques, orchestrating the pipeline on Mage, and ultimately creating a dashboard using Looker Studio.
Python, GCP (Storage, Compute Engine, BigQuery), Mage, Looker Studio
Developed and implemented an end-to-end ETL pipeline for processinsg NYC Trip Record data. The pipeline encompassed extracting raw data, performing data transformation using Python, applying fact and dimensional data modelling techniques, orchestrating the pipeline on Mage, and ultimately creating a dashboard using Looker Studio.
Python, GCP (Storage, Compute Engine, BigQuery), Mage, Looker Studio
Developed and implemented an end-to-end ETL pipeline for processinsg NYC Trip Record data. The pipeline encompassed extracting raw data, performing data transformation using Python, applying fact and dimensional data modelling techniques, orchestrating the pipeline on Mage, and ultimately creating a dashboard using Looker Studio.
Made with πͺ & π by Diogo Silva
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Welcome to my portfolio! Here you can find all my projects in the data universe.