In this hands-on lab scenario, you are a data engineer for Awesome Company. You have been tasked with creating a stream processing solution in Azure that will analyze crowdsourced weather information and provide running averages. Previously, you have provisioned an Azure Data Lake Storage Gen2 account to hold the uploaded files, and now you need to configure the appropriate Azure services to both view and store the average temperatures per country in near-real time. Performing the actions of this hands-on lab will help you become familiar with building a complete stream processing solution using Azure services.
Learning Objectives
Successfully complete this lab by achieving the following learning objectives:
- Simulate Data Uploads
Use Azure Cloud Shell within the Azure portal to run the file creation simulator located on GitHub.
- Process Streaming Data with Azure Stream Analytics
Configure an Azure Stream Analytics job to obtain the average temperatures of each country across a three-minute tumbling window. Have the output stored in an Azure Cosmos DB database.
- Verify the Data
Query the Azure Cosmos DB database to make sure the correct information is being stored.
