In part 2 of the series about Change Data Capture (CDC) in Azure Data Explorer, we look at another approach on how to handle data when only changes from the device to the cloud are sent.
Change Data Capture (CDC) is a design pattern to only track the changes in data. There are several ways this could be implemented. In IoT solutions, the Change Data Capture (CDC) pattern is used, to only send changes from the device to the cloud. But how to deal with this data in Azure Data Explorer for further analysis?
Located someone in Azure Data Explorer with the use of a function and a scatter plot based on an IP-address.
What if you have an Azure IoT solution and recently added Azure Data Explorer (ADX), and you also want to ingest your historical data. Then LightIngest might be the solution, a lightweight tool for importing data into Azure Data Explore.
It is possible to create an Azure Data Explorer cluster using ARM or Bicep templates. The only thing lacking is the ability to integrate ADX dashboards into Azure DevOps enabling Continuous Integration / Continuous Delivery, or is it?
Azure Data Explorer is a fast and powerful Azure service for analyzing real-time data. Let’s see how to create a dashboard and make it available for users who may not be familiar with Kusto.