A retail company uses Azure Synapse Analytics to store sales data. The data team wants to create a pipeline that loads data from an on-premises ERP system into Synapse every hour. They also want to monitor the pipeline's success and failure. What should you use?

Use Azure Data Factory with a self-hosted integration runtime and a scheduled trigger, and monitor using Azure Monitor.

Use Azure Logic Apps with a recurrence trigger and the SQL connector to load data.

Use Azure Databricks with a scheduled job to read from the ERP and write to Synapse.

Use Azure Synapse pipelines directly, but they do not support on-premises sources.

A company has an existing Azure Synapse Analytics workspace. They need to load data from a third-party REST API into a dedicated SQL pool. The API has rate limits and requires authentication. The team wants to use Azure Data Factory for orchestration. What should you do?

Create a linked service for the REST API in ADF, use a Copy activity, and handle pagination and throttling with retry policies.

Use Azure Data Factory with a Web activity to call the API and then a Stored Procedure activity to load data.

Use a Logic App to call the API and write to Synapse.

Use Azure Functions to call the API and load data into Synapse.

A media company uses Azure Databricks to process video metadata and run machine learning models to recommend content. The data science team wants to use Python and Spark to train models on large datasets. They also want to schedule the training jobs to run nightly. What should you do?

Use Azure Logic Apps to run the Databricks notebook on a schedule.

Use Azure Synapse Analytics pipelines to run the notebook, but only if the data is stored in Synapse.

Create a Databricks notebook with the training code and use Azure Data Factory to schedule the notebook execution.

Manually run the notebook each night from the Databricks workspace.

Azure Solutions Architect Expert

Domain 2Objective 3

Design Data Integration AZ-305 Practice Questions (Page 5)

Part of the Design data storage solutions domain, which makes up ~25% of our current practice bank. Microsoft does not publish an official question count, but from its 120-minute exam (~50–80 total, ~13–20 in this domain), expect 4–7 from this objective — we provide 28 practice questions to prepare you well beyond it. (estimate)

28questions here

6free pages

7concepts

Questions 21–25

21foundation · easy
A company wants to automate a workflow that monitors a shared mailbox for emails with attachments, saves those attachments to a network share, and then posts a notification to a Microsoft Teams channel. The workflow must work with on-premises systems and cloud services. Which Azure service should be used to build this workflow?
Select an answer first
22application · medium
A retail company uses Azure Synapse Analytics to store sales data. The data team wants to create a pipeline that loads data from an on-premises ERP system into Synapse every hour. They also want to monitor the pipeline's success and failure. What should you use?
Select an answer first
23foundation · easy
A data engineer needs to build a pipeline that copies data from an on-premises SQL Server to Azure Blob Storage every hour, and then runs a stored procedure to transform the data. Which Azure Data Factory component is used to define the sequence of these activities?
Select an answer first
24expert · hard
A company has an existing Azure Synapse Analytics workspace. They need to load data from a third-party REST API into a dedicated SQL pool. The API has rate limits and requires authentication. The team wants to use Azure Data Factory for orchestration. What should you do?
Select an answer first
25application · medium
A media company uses Azure Databricks to process video metadata and run machine learning models to recommend content. The data science team wants to use Python and Spark to train models on large datasets. They also want to schedule the training jobs to run nightly. What should you do?
Select an answer first

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Design Data Integration AZ-305 Practice Questions (Page 5)

Questions 21–25

A retail company uses Azure Synapse Analytics to store sales data. The data team wants to create a pipeline that loads data from an on-premises ERP system into Synapse every hour. They also want to monitor the pipeline's success and failure. What should you use?

A data engineer needs to build a pipeline that copies data from an on-premises SQL Server to Azure Blob Storage every hour, and then runs a stored procedure to transform the data. Which Azure Data Factory component is used to define the sequence of these activities?

A company has an existing Azure Synapse Analytics workspace. They need to load data from a third-party REST API into a dedicated SQL pool. The API has rate limits and requires authentication. The team wants to use Azure Data Factory for orchestration. What should you do?

A media company uses Azure Databricks to process video metadata and run machine learning models to recommend content. The data science team wants to use Python and Spark to train models on large datasets. They also want to schedule the training jobs to run nightly. What should you do?

Keep studying — Design data storage solutions