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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
Batch ETL pipeline project on GCP to load and transform daily flight data using Spark to update tables in BigQuery. The pipeline is automated using Airflow.
Creating a robust and scalable data pipeline on Google Cloud Platform (GCP) to monitor and analyze stock performance. Leveraging the power of GCP's data processing and storage services, a comprehensive solution has been built to efficiently collect, process, and visualize stock data.
This GitHub repository serves as a comprehensive platform for managing and showcasing my data engineering projects and assessments throughout my final semester at Alt School Africa. Designed to foster collaboration, organization, and continuous improvement, this repository is the backbone of my academic journey in data engineering.
This project aims to migrate data from MongoDB to Google Cloud Storage (GCS) and BigQuery automatically. It enables businesses to easily transfer and analyze the data in the cloud, improving data and cost management.