Free DP-203 Exam Braindumps
Data Engineering on Microsoft Azure (Replaced with DP-700) Questions 53–57 (page: 37)

Updated On: 10-Feb-2026

DRAG DROP (Drag and Drop is not supported)
You are designing an Azure Data Lake Storage Gen2 structure for telemetry data from 25 million devices distributed across seven key geographical regions. Each minute, the devices will send a JSON payload of metrics to Azure Event Hubs.
You need to recommend a folder structure for the data. The solution must meet the following requirements: Data engineers from each region must be able to build their own pipelines for the data of their respective region only.

The data must be processed at least once every 15 minutes for inclusion in Azure Synapse Analytics serverless SQL pools.

How should you recommend completing the structure? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: {raw/regionID}
Box 2: {YYYY}/{MM}/{DD}/{HH}/{mm}
Box 3: {deviceID}


Reference:

https://github.com/paolosalvatori/StreamAnalyticsAzureDataLakeStore/blob/master/README.md



HOTSPOT (Drag and Drop is not supported)
You are implementing an Azure Stream Analytics solution to process event data from devices.
The devices output events when there is a fault and emit a repeat of the event every five seconds until the fault is resolved. The devices output a heartbeat event every five seconds after a previous event if there are no faults present.
A sample of the events is shown in the following table.


You need to calculate the uptime between the faults.
How should you complete the Stream Analytics SQL query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: WHERE EventType='HeartBeat'
Box 2: ,TumblingWindow(Second, 5)
Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals.
The following diagram illustrates a stream with a series of events and how they are mapped into 10-second tumbling windows.

Incorrect Answers:
,SessionWindow.. : Session windows group events that arrive at similar times, filtering out periods of time where there is no data.


Reference:

https://docs.microsoft.com/en-us/stream-analytics-query/session-window-azure-stream-analytics https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics



You are creating a new notebook in Azure Databricks that will support R as the primary language but will also support Scala and SQL.
Which switch should you use to switch between languages?

  1. %<language>
  2. @<Language >
  3. \\[<language >]
  4. \\(<language >)

Answer(s): A

Explanation:

To change the language in Databricks?cells to either Scala, SQL, Python or R, prefix the cell with ?%?, followed by the language.
%python //or r, scala, sql


Reference:

https://www.theta.co.nz/news-blogs/tech-blog/enhancing-digital-twins-part-3-predictive-maintenance-withazure-databricks



You have an Azure Data Factory pipeline that performs an incremental load of source data to an Azure Data Lake Storage Gen2 account.
Data to be loaded is identified by a column named LastUpdatedDate in the source table. You plan to execute the pipeline every four hours.

You need to ensure that the pipeline execution meets the following requirements:
-Automatically retries the execution when the pipeline run fails due to concurrency or throttling limits.
-Supports backfilling existing data in the table.

Which type of trigger should you use?

  1. event
  2. on-demand
  3. schedule
  4. tumbling window

Answer(s): D

Explanation:

In case of pipeline failures, tumbling window trigger can retry the execution of the referenced pipeline automatically, using the same input parameters, without the user intervention. This can be specified using the property "retryPolicy" in the trigger definition.


Reference:

https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-tumbling-window-trigger



You are designing a solution that will copy Parquet files stored in an Azure Blob storage account to an Azure Data Lake Storage Gen2 account.
The data will be loaded daily to the data lake and will use a folder structure of {Year}/{Month}/{Day}/. You need to design a daily Azure Data Factory data load to minimize the data transfer between the two accounts.

Which two configurations should you include in the design? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point

  1. Specify a file naming pattern for the destination.
  2. Delete the files in the destination before loading the data.
  3. Filter by the last modified date of the source files.
  4. Delete the source files after they are copied.

Answer(s): A,C

Explanation:

Copy only the daily files by using filtering.


Reference:

https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-data-lake-storage



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