This is the second big project from the course Data Engineering with Azure specialization on Udacity that I've recently completed. If you want to read about my first project, you can find it in this blog.
Data Engineering with Azure could be your gateway to unlocking thrilling projects like building a comprehensive data lake solution. In this blog post, we will unravel the great journey of developing a data lake solution for Divvy bikeshare, a bike sharing program based in Chicago, Illinois, USA.
You can find the code related to this project in my GitHub repository.
Project Overview
Divvy bike share is a popular program that allows riders in Chicago to access bikes via kiosks or a mobile application. The anonymized bike trip data from Divvy is made publicly available by the City of Chicago for analysis, forming the foundation of this data engineering project.
The goal of this project was to develop a data lake solution using Azure Databricks, using a lake house architecture. The objectives included designing a star schema, importing data into Azure Databricks using Delta Lake for creating bronze and gold data stores, and transforming the data into the star schema for the gold data store.
If you are interested and want to read the whole story, go to this link
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