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DP-203 Pdf Braindumps, DP-203 Customized Lab Simulation
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Microsoft DP-203 (Data Engineering on Microsoft Azure) certification exam is an industry-recognized credential that validates a candidate's knowledge and expertise in designing and implementing data solutions on the Microsoft Azure platform. DP-203 Exam is intended for data professionals who work with Azure technologies to design and implement data solutions, including data architects, data engineers, and business intelligence professionals.
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Microsoft DP-203 certification exam is intended for data engineers who work with data scientists, data analysts, and business stakeholders to implement data solutions on the Microsoft Azure platform. DP-203 exam covers various topics such as Azure data storage, Azure data processing, Azure data integration, and data transformation. It also tests your knowledge of key Azure services such as Azure Data Factory, Azure Synapse Analytics, and Azure Stream Analytics.
Microsoft DP-203 Exam is suitable for those who have experience with Microsoft Azure and want to specialize in data engineering. DP-203 exam covers a wide range of topics such as data processing, data storage, data transformation, and data integration. It tests the candidate's ability to design, implement, and monitor data processing solutions on Azure.
Microsoft Data Engineering on Microsoft Azure Sample Questions (Q227-Q232):
NEW QUESTION # 227
You need to design an analytical storage solution for the transactional data. The solution must meet the sales transaction dataset requirements.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, text, application, table Description automatically generated
Box 1: Round-robin
Round-robin tables are useful for improving loading speed.
Scenario: Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month.
Box 2: Hash
Hash-distributed tables improve query performance on large fact tables.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-distribu
NEW QUESTION # 228
A company has a real-time data analysis solution that is hosted on Microsoft Azure. The solution uses Azure Event Hub to ingest data and an Azure Stream Analytics cloud job to analyze the data. The cloud job is configured to use 120 Streaming Units (SU).
You need to optimize performance for the Azure Stream Analytics job.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Implement query parallelization by partitioning the data output.
- B. Implement query parallelization by partitioning the data input.
- C. Implement Azure Stream Analytics user-defined functions (UDF).
- D. Implement event ordering.
- E. Scale the SU count for the job up.
- F. Scale the SU count for the job down.
Answer: B,E
NEW QUESTION # 229
You have a self-hosted integration runtime in Azure Data Factory.
The current status of the integration runtime has the following configurations:
Status: Running
Type: Self-Hosted
Running / Registered Node(s): 1/1
High Availability Enabled: False
Linked Count: 0
Queue Length: 0
Average Queue Duration. 0.00s
The integration runtime has the following node details:
Name: X-M
Status: Running
Available Memory: 7697MB
CPU Utilization: 6%
Network (In/Out): 1.21KBps/0.83KBps
Concurrent Jobs (Running/Limit): 2/14
Role: Dispatcher/Worker
Credential Status: In Sync
Use the drop-down menus to select the answer choice that completes each statement based on the information presented.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime
NEW QUESTION # 230
Which Azure Data Factory components should you recommend using together to import the daily inventory data from the SQL server to Azure Data Lake Storage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 231
You plan to create an Azure Synapse Analytics dedicated SQL pool.
You need to minimize the time it takes to identify queries that return confidential information as defined by the company's data privacy regulations and the users who executed the queues.
Which two components should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. dynamic data masking for columns that contain confidential information
- B. sensitivity-classification labels applied to columns that contain confidential information
- C. audit logs sent to a Log Analytics workspace
- D. resource tags for databases that contain confidential information
Answer: B,C
Explanation:
Explanation
A: You can classify columns manually, as an alternative or in addition to the recommendation-based classification:
* Select Add classification in the top menu of the pane.
* In the context window that opens, select the schema, table, and column that you want to classify, and the information type and sensitivity label.
* Select Add classification at the bottom of the context window.
C: An important aspect of the information-protection paradigm is the ability to monitor access to sensitive data. Azure SQL Auditing has been enhanced to include a new field in the audit log called data_sensitivity_information. This field logs the sensitivity classifications (labels) of the data that was returned by a query. Here's an example:
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview
NEW QUESTION # 232
......
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