What is the Session About?

The session is about exploring how Azure can be used to power data engineering and data science workflows. Specifically, the session will cover the core Azure services that enable data engineering and data science workloads, including Azure Data Factory, Azure Database, and Azure Machine Learning. The session is designed to be hands-on, with attendees being guided through the process of setting up and configuring data pipelines, building scalable data processing and analytics workflows, and building, training, and deploying machine learning models at scale using Azure. By the end of the session, attendees will have a solid understanding of how to use Azure to power their data engineering and data science workflows.

Who is it aimed at?

This session is aimed at enthusiastic students, data engineers, data scientists, and IT professionals who are interested in exploring data workloads & solutions in the cloud. No prior experience with Azure is required, but participants should have a basic understanding of Data & Machine Learning concepts

Why should you attend?

If you are a developer or a software engineer who is uncertain about how data engineering fits into machine learning & the cloud, this session is for you. It's common to view data engineering as a separate art that's practiced only by elite developers, but this session will help dispel those doubts. By attending, you'll learn how data engineering & machine learning can be integrated with azure and how they can be used to enhance decision making.