You have an Azure Event Hubs data source that contains weather data. You ingest the data from the data source by using an eventstream named Eventstream1. Eventstream1 uses a lakehouse as the…

This question tests knowledge of Microsoft Fabric Eventstream's built-in data transformation and filtering capabilities before routing data to a destination such as a Lakehouse.

Design and implement data ingestion and transformation

Question

You have an Azure Event Hubs data source that contains weather data. You ingest the data from the data source by using an eventstream named Eventstream1. Eventstream1 uses a lakehouse as the destination.
You need to batch ingest only rows from the data source where the City attribute has a value of Kansas. The filter must be added before the destination. The solution must minimize development effort.
What should you use for the data processor and filtering? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Explanation

This question tests knowledge of Microsoft Fabric Eventstream's built-in data transformation and filtering capabilities before routing data to a destination such as a Lakehouse.

Approach. The correct approach uses the built-in 'Filter' operation available in Eventstream's event processor (the no-code editor within Eventstream1). You add a 'Filter' transformation step between the source and the Lakehouse destination, setting the condition 'City equals Kansas'. This requires zero custom code and no external services, minimizing development effort. The data processor to use is the Eventstream built-in event processor (also called the 'Event processor editor'), and the filtering mechanism is the native 'Filter' transform node within that editor.

Concept tested. Microsoft Fabric Eventstream event processing - specifically, using the built-in no-code event processor editor to apply a Filter transformation on a streaming attribute (City = 'Kansas') before data lands in a Lakehouse destination, rather than using Azure Stream Analytics, custom Spark code, or post-ingestion filtering.

Reference. https://learn.microsoft.com/en-us/fabric/real-time-intelligence/event-streams/process-events-using-event-processor-editor

Topics

#Microsoft Fabric Eventstream#Data Processor#Streaming Data Filtering#Lakehouse Ingestion

Community Discussion

No community discussion yet for this question.

Full DP-700 Practice