In this session we'll cover how Azure Event Grid can be used to unify and automate your data loading workflows, including how messages can be utilized to communicate changes in state in the flow of data.
Azure Event Grid can for instance be used to monitor changes in state within the layers of a data lake and trigger downstream processing tasks. For example, when new data is added to the raw data layer, Event Grid can be configured to send a message indicating that new data has been added. This message can then be used to trigger the next stage of the data processing pipeline, such as data cleaning or enrichment.
Messages can also be used to provide additional context and metadata about the changes in state within the data lake. For example, a message can include information about the type of data that was added, the timestamp of the data, and the source of the data.
By utilizing messages to communicate changes in state within the data lake, Azure Event Grid enables a more efficient and streamlined data processing pipeline. Data loading workflows can be automated and triggered in real-time, reducing manual intervention and improving overall efficiency.
Within an Event Grid you can configure various topics, so that you can control downstream targeted audiences, who then again can filter on said topic, if they need only react to a subset of the messages.

We will look at how to setup and configure an Event Grid, go over how to send messages to different topics, we will cover configuring an Azure Function to react to specific messages as well as logging all messages into a data lake.

By attending this session, you will get an overall insight into how Event Grids work and see some applied use cases.