- Lab
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- Data
Configure and Run a Job in Azure Stream Analytics
Almost every organization with a presence in the cloud will find themselves in a need of robust tooling to handle real-time streaming data. In this lab, you will have an opportunity to build a simple streaming pipeline with pre-deployed resources in Azure. Imagine you work for a government transportation department, and you have been tasked with capturing traffic passing through toll booths on a newly opened roadway. The team has already figured out a way to connect the toll booth sensors to an Azure Event Hub. The next step is to develop a low-code or no-code solution to process that data and make it available to downstream applications — both operational and analytical. Using a pre-deployed set of resources, you will configure an Azure Stream Analytics job to ingest data from an Event Hub instance, transform the data, and deliver it to blob storage.
Lab Info
Table of Contents
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Challenge
Navigate to the Data Explorer in the pre-deployed Azure Event Hub
Examine the shape of the sample data related to toll booths.
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Challenge
Configure the Azure Stream Analytics Job
- Use the pre-deployed Azure Event Hub as the job input.
- Use the pre-deployed Azure Storage container as the job output.
- Using observations of the sample data, alter the default query to perform a simple transformation on the inbound data.
- Start the job.
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Challenge
Test and validate the job
- Send sample events from the Event Hub, using the Data Explorer.
- Confirm that the appropriately transformed data is stored in a blob in the Azure Storage container.
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