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Microsoft DP-203 certification exam is a great way to showcase your expertise in data engineering on the Azure platform. By passing DP-203 exam, you will gain recognition for your skills and knowledge, which can help you advance your career in the field of data engineering. Data Engineering on Microsoft Azure certification is also valuable for organizations that want to hire data engineers with the expertise to design and implement scalable data solutions on Azure.



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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q200-Q205):

NEW QUESTION # 200
You are creating an Azure Data Factory data flow that will ingest data from a CSV file, cast columns to specified types of data, and insert the data into a table in an Azure Synapse Analytic dedicated SQL pool. The CSV file contains three columns named username, comment, and date.
The data flow already contains the following:
A source transformation.
A Derived Column transformation to set the appropriate types of data.
A sink transformation to land the data in the pool.
You need to ensure that the data flow meets the following requirements:
All valid rows must be written to the destination table.
Truncation errors in the comment column must be avoided proactively.
Any rows containing comment values that will cause truncation errors upon insert must be written to a file in blob storage.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

* A. To the data flow, add a sink transformation to write the rows to a file in blob storage.
* B. To the data flow, add a Conditional Split transformation to separate the rows that will cause truncation errors.
* C. Add a select transformation to select only the rows that will cause truncation errors.
* D. To the data flow, add a filter transformation to filter out rows that will cause truncation errors.
Answer: A,B

Explanation:
Explanation
B: Example:
1. This conditional split transformation defines the maximum length of "title" to be five. Any row that is less than or equal to five will go into the GoodRows stream. Any row that is larger than five will go into the BadRows stream.

2. This conditional split transformation defines the maximum length of "title" to be five. Any row that is less than or equal to five will go into the GoodRows stream. Any row that is larger than five will go into the BadRows stream.
A:
3. Now we need to log the rows that failed. Add a sink transformation to the BadRows stream for logging.
Here, we'll "auto-map" all of the fields so that we have logging of the complete transaction record. This is a text-delimited CSV file output to a single file in Blob Storage. We'll call the log file "badrows.csv".

4. The completed data flow is shown below. We are now able to split off error rows to avoid the SQL truncation errors and put those entries into a log file. Meanwhile, successful rows can continue to write to our target database.

Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-data-flow-error-rows

NEW QUESTION # 201
You have an Azure subscription that contains an Azure Synapse Analytics dedicated SQL pool named Pool1.
You have the queries shown in the following table.

You are evaluating whether to enable result set caching for Pool1. Which query results will be cached if result set caching is enabled?

* A. Query1 only
* B. Query 1, Query2, and Query3 only
* C. Query2 only
* D. Query 1 and Query2 only
* E. Query1 and Query3 only
Answer: D

NEW QUESTION # 202
You need to implement versioned changes to the integration pipelines. The solution must meet the data integration requirements.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.


Answer:

Explanation:

1 - Create a repository and a main branch
2 - Create a feature branch
3 - Create a pull request
4 - Merge changes
5 - Publish changes
Reference:
https://docs.microsoft.com/en-us/azure/devops/pipelines/repos/pipeline-options-for-git

NEW QUESTION # 203
You need to integrate the on-premises data sources and Azure Synapse Analytics. The solution must meet the data integration requirements.
Which type of integration runtime should you use?

* A. Azure integration runtime
* B. Azure-SSIS integration runtime
* C. self-hosted integration runtime
Answer: B

NEW QUESTION # 204
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 are designing an Azure Stream Analytics solution that will analyze Twitter data.
You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once.
Solution: You use a tumbling window, and you set the window size to 10 seconds.
Does this meet the goal?

* A. No
* B. Yes
Answer: B

Explanation:
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.

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

NEW QUESTION # 205
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