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You have an Azure Data Lake Storage account that contains a staging zone.
You need to design a daily process to ingest incremental data from the staging zone, transform the data by executing an R script, and then insert the transformed data into a data warehouse in Azure Synapse Analytics.
Solution: You use an Azure Data Factory schedule trigger to execute a pipeline that copies the data to a staging table in the data warehouse, and then uses a stored procedure to execute the R script.
Does this meet the goal?

A. Yes

B. No












 

Suggested Answer: A

If you need to transform data in a way that is not supported by Data Factory, you can create a custom activity with your own data processing logic and use the activity in the pipeline.
Note: You can use data transformation activities in Azure Data Factory and Synapse pipelines to transform and process your raw data into predictions and insights at scale.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/transform-data

This question is in DP-203 Data Engineering on Microsoft Azure Exam
For getting Microsoft Certified: Azure Data Engineer Associate Certificate


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