📝 In this repo, we've sliced and diced a massive dataset into smaller, more manageable dimensions using some pretty nifty ETL techniques. We then used these dimensions to create two fact tables, factorderlines and factorders.
💾 To handle the database, we went with the trusty Azure, and for data visualization, we chose the ever-popular PowerBI.
📊 Check out our main file, "main.ipynb", to see our ETL process in action and how we transformed the data. We've also included our "dim" and "fact" tables so you can see how we organized our data for optimal analysis.
🤖 We hope this repo inspires you and gives you some ideas for your own data warehousing projects. Come join the fun of data slicing and dicing with us! 🤖