Football Data Analytics | Azure End To End Data Engineering Project

In this tutorial, we dive deep into the world of football data engineering. We'll walk through the entire process of extracting football data from Wikipedia using Apache Airflow, storing it in Azure Data Lake, migrating the data with Azure Data Factory, querying with Azure Synapse, and finally visualizing our findings in Tableau.

🔗 Timestamps:
0:00 - Introduction
3:15 - Setting up the Infrastructure
8:45 - Extracting data from Wikipedia
35:00 - Cleaning the Data
47:00 - Transforming the Data
53:00 - Enriching the dataset with Lat and Long
1:01:11 - Writing the cleaned data to file
1:14:40 - Outro

🌟 Please LIKE ❤️ and SUBSCRIBE for more AMAZING content! 🌟

📚 Resources & Links:
0. Code: https://github.com/airscholar/FootballDataEngineering.git
1. Apache Airflow Documentation: https://airflow.apache.org/docs/
2. Azure Data Lake Documentation: https://learn.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction
3. Azure Data Factory Documentation: https://learn.microsoft.com/en-us/azure/data-factory/
4. Azure Synapse Documentation: https://learn.microsoft.com/en-us/azure/synapse-analytics/overview-what-is
5. Medium Link: https://medium.com/@yusuf.ganiyu/football-data-analytics-from-wikipedia-through-azure-and-apache-airflow-to-tableau-5edeb035cc0b

⚡️Tags ⚡️
Football, Data Engineering, Apache Airflow, Docker, Azure Data Lake, Azure Data Factory, Azure Synapse, Tableau, Data Visualization, Wikipedia Data Extraction, Tutorial

⚡️Hashtags ⚡️
#FootballData #DataEngineering #ApacheAirflow #Azure #Tableau #WikipediaData #DataVisualization #docker