Microsoft DP-203 Exam

You have two Azure Blob Storage accounts named account1 and account2?

You plan to create an Azure Data Factory pipeline that will use scheduled intervals to replicate newly created or modified blobs from account1 to account?

You need to recommend a solution to implement the pipeline. The solution must meet the following requirements:

* Ensure that the pipeline only copies blobs that were created of modified since the most recent replication event.

* Minimize the effort to create the pipeline.

What should you recommend?

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You have two Azure Blob Storage accounts named account1 and account2?

You plan to create an Azure Data Factory pipeline that will use scheduled intervals to replicate newly created or modified blobs from account1 to account?

You need to recommend a solution to implement the pipeline. The solution must meet the following requirements:

* Ensure that the pipeline only copies blobs that were created of modified since the most recent replication event.

* Minimize the effort to create the pipeline.

What should you recommend?

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You have an Azure data factory named ADM that contains a pipeline named Pipelwe1

Pipeline! must execute every 30 minutes with a 15-minute offset.

Vou need to create a trigger for Pipehne1. The trigger must meet the following requirements:

* Backfill data from the beginning of the day to the current time.

* If Pipeline1 fairs, ensure that the pipeline can re-execute within the same 30-mmute period.

* Ensure that only one concurrent pipeline execution can occur.

* Minimize de4velopment and configuration effort

Which type of trigger should you create?

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Note: The 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 dairy 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 a mapping data low. and then inserts the data into the data warehouse.

Does this meet the goal?

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You are building a data flow in Azure Data Factory that upserts data into a table in an Azure Synapse Analytics dedicated SQL pool.

You need to add a transformation to the data flow. The transformation must specify logic indicating when a row from the input data must be upserted into the sink.

Which type of transformation should you add to the data flow?

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