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Microsoft DP-203 Practice Test - Questions Answers, Page 19

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Question 181

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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?

Yes
Yes
No
No
Suggested answer: B

Explanation:

If you need to transform data in a way that is not supported by Data Factory, you can create a custom activity, not an Azure Databricks notebook, with your own data processing logic and use the activity in the pipeline. You can create a custom activity to run R scripts on your HDInsight cluster with R installed.

Microsoft DP-203 image Question 5 explanation 89647 10022024015850000000

Reference:

https://docs.microsoft.com/en-US/azure/data-factory/transform-data

asked 02/10/2024
David Ezejimofor
36 questions

Question 182

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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 mapping data flow, and then inserts the data into the data warehouse. Does this meet the goal?

Yes
Yes
No
No
Suggested answer: A

Explanation:


asked 02/10/2024
Mitchell Mansfield
28 questions

Question 183

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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 schedule an Azure Databricks job that executes an R notebook, and then inserts the data into the data warehouse. Does this meet the goal?

Yes
Yes
No
No
Suggested answer: A

Explanation:


asked 02/10/2024
Saikhantsetseg Donnelly
38 questions

Question 184

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You plan to create an Azure Data Factory pipeline that will include a mapping data flow. You have JSON data containing objects that have nested arrays. You need to transform the JSON-formatted data into a tabular dataset. The dataset must have one row for each item in the arrays. Which transformation method should you use in the mapping data flow?

new branch
new branch
unpivot
unpivot
alter row
alter row
flatten
flatten
Suggested answer: D

Explanation:

Use the flatten transformation to take array values inside hierarchical structures such as JSON and unroll them into individual rows. This process is known as denormalization.

Reference:

https://docs.microsoft.com/en-us/azure/data-factory/data-flow-flatten

asked 02/10/2024
Vadym Popov
39 questions

Question 185

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You use Azure Stream Analytics to receive Twitter data from Azure Event Hubs and to output the data to an Azure Blob storage account. You need to output the count of tweets during the last five minutes every five minutes. Each tweet must only be counted once. Which windowing function should you use?

a five-minute Sliding window
a five-minute Sliding window
a five-minute Session window
a five-minute Session window
a five-minute Hopping window that has a one-minute hop
a five-minute Hopping window that has a one-minute hop
a five-minute Tumbling window
a five-minute Tumbling window
Suggested answer: D

Explanation:

Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions

asked 02/10/2024
om Kumar
42 questions

Question 186

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You are planning a streaming data solution that will use Azure Databricks. The solution will stream sales transaction data from an online store. The solution has the following specifications:

The output data will contain items purchased, quantity, line total sales amount, and line total tax amount. Line total sales amount and line total tax amount will be aggregated in Databricks. Sales transactions will never be updated. Instead, new rows will be added to adjust a sale. You need to recommend an output mode for the dataset that will be processed by using Structured Streaming. The solution must minimize duplicate data. What should you recommend?

Update
Update
Complete
Complete
Append
Append
Suggested answer: B

Explanation:

By default, streams run in append mode, which adds new records to the table.https://docs.databricks.com/delta/delta-streaming.html

asked 02/10/2024
Emanuel Sifuentes
43 questions

Question 187

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You have an enterprise data warehouse in Azure Synapse Analytics named DW1 on a server named Server1. You need to determine the size of the transaction log file for each distribution of DW1. What should you do?

On DW1, execute a query against the sys.database_files dynamic management view.
On DW1, execute a query against the sys.database_files dynamic management view.
From Azure Monitor in the Azure portal, execute a query against the logs of DW1.
From Azure Monitor in the Azure portal, execute a query against the logs of DW1.
Execute a query against the logs of DW1 by using theGet-AzOperationalInsightsSearchResult PowerShell cmdlet.
Execute a query against the logs of DW1 by using theGet-AzOperationalInsightsSearchResult PowerShell cmdlet.
On the master database, execute a query against the sys.dm_pdw_nodes_os_performance_counters dynamic management view.
On the master database, execute a query against the sys.dm_pdw_nodes_os_performance_counters dynamic management view.
Suggested answer: A

Explanation:

For information about the current log file size, its maximum size, and the autogrow option for the file, you can also use the size, max_size, and growth columns for that log file in sys.database_files.

Reference:

https://docs.microsoft.com/en-us/sql/relational-databases/logs/manage-the-size-of-the-transaction-log-file

asked 02/10/2024
Piyush Zope
41 questions

Question 188

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You are designing an anomaly detection solution for streaming data from an Azure IoT hub. The solution must meet the following requirements:

Send the output to Azure Synapse.

Identify spikes and dips in time series data.

Minimize development and configuration effort.

Which should you include in the solution?

Azure Databricks
Azure Databricks
Azure Stream Analytics
Azure Stream Analytics
Azure SQL Database
Azure SQL Database
Suggested answer: B

Explanation:

You can identify anomalies by routing data via IoT Hub to a built-in ML model in Azure Stream Analytics.

Reference:

https://docs.microsoft.com/en-us/learn/modules/data-anomaly-detection-using-azure-iot-hub/

asked 02/10/2024
Ed Quinn
31 questions

Question 189

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A company uses Azure Stream Analytics to monitor devices.

The company plans to double the number of devices that are monitored. You need to monitor a Stream Analytics job to ensure that there are enough processing resources to handle the additional load. Which metric should you monitor?

Early Input Events
Early Input Events
Late Input Events
Late Input Events
Watermark delay
Watermark delay
Input Deserialization Errors
Input Deserialization Errors
Suggested answer: A
asked 02/10/2024
Simon Tam
35 questions

Question 190

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You have an Azure Stream Analytics job.

You need to ensure that the job has enough streaming units provisioned. You configure monitoring of the SU % Utilization metric.

Which two additional metrics should you monitor? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

Backlogged Input Events
Backlogged Input Events
Watermark Delay
Watermark Delay
Function Events
Function Events
Out of order Events
Out of order Events
Late Input Events
Late Input Events
Suggested answer: A, B

Explanation:

To react to increased workloads and increase streaming units, consider setting an alert of 80% on the SU Utilization metric. Also, you can use watermark delay and backlogged events metrics to see if there is an impact. Note: Backlogged Input Events: Number of input events that are backlogged. A non-zero value for this metric implies that your job isn't able to keep up with the number of incoming events. If this value is slowly increasing or consistently non-zero, you should scale out your job, by increasing the SUs.

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitoring

asked 02/10/2024
Guillaume Deterville
46 questions
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