Azure provides cool services for data management, making advanced data pipelines look very simple. However, making different services work well together requires a substantial amount of time.
A few weeks ago I gave a session at Vilnius Data Platform Meetup on Azure Stream Analytics: Hands-on exercises on processing car’s telemetry events. I decided to structure the demo a bit and publish it on GitHub.
The project aims to simplify Azure Big Data environment setup. Involved Azure PaaS services require different development and deployment steps, and this initiative is a set of suggestions for improving the overall development experience. I use car telemetry data as an example.
You can find more information about Big Data architectural style in Azure here.
Azure offers many different PaaS services for stream and batch workloads. Since HDInsight offerings require extra effort and don’t provide multitenancy, this project only focuses on full scope PaaS. Below you find the architecture and involved services. Green dots mark currently utilized services.
