DP-203 · Question #284
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…
The correct answer is A. Yes. You can execute R code in a notebook, and then call it from Data Factory. You can check it at "Databricks Notebook activity" header: https://docs.microsoft.com/en-US/azure/data-factory/transform-data https://docs.microsoft.com/en-us/azure/databricks/spark/latest/sparkr/overview
Question
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. 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 executes an Azure Databricks notebook, and then inserts the data into the data warehouse. Does this meet the goal?
Options
- AYes
- BNo
How the community answered
(28 responses)- A86% (24)
- B14% (4)
Explanation
You can execute R code in a notebook, and then call it from Data Factory. You can check it at "Databricks Notebook activity" header: https://docs.microsoft.com/en-US/azure/data-factory/transform-data https://docs.microsoft.com/en-us/azure/databricks/spark/latest/sparkr/overview
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