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.
English
Last updated
Thu, 04-Apr-2024
Welcome to an immersive journey into football data engineering.
This course is meticulously designed to guide you through the multifaceted world of data extraction, storage, migration, querying, and visualization.
Starting with Apache Airflow, you'll learn to extract football-centric data from Wikipedia. From there, we delve into the Azure ecosystem, storing our data in Azure Data Lake, and seamlessly migrating it using Azure Data Factory. The querying power of Azure Synapse comes in next, allowing you to dive deep into the data. At the end of this journey is the visualization of our findings in Tableau, providing a holistic view of the football world. With hands-on examples, expert insights, and a plethora of resources, this tutorial is your ultimate guide to football data engineering.
Data Mastery Lab is an online learning and teaching platform for data engineering, data science, data analytics, machine learning and artificial intelligence.
