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The DP-203 exam covers a wide range of topics related to data engineering, including data storage and processing, data integration, data transformation, data security, and data management. Candidates are tested on their ability to design and implement data processing systems, as well as their proficiency in using Azure data services such as Azure Data Factory, Azure Stream Analytics, and Azure Databricks. DP-203 Exam also evaluates candidates' knowledge of data warehousing, big data technologies, and machine learning.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q66-Q71):

NEW QUESTION # 66
You have a data model that you plan to implement in a data warehouse in Azure Synapse Analytics as shown in the following exhibit.

All the dimension tables will be less than 2 GB after compression, and the fact table will be approximately 6 TB.
Which type of table should you use for each table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 67
You have an Azure Data Factory instance named ADF1 and two Azure Synapse Analytics workspaces named WS1 and WS2.
ADF1 contains the following pipelines:
P1: Uses a copy activity to copy data from a nonpartitioned table in a dedicated SQL pool of WS1 to an Azure Data Lake Storage Gen2 account P2: Uses a copy activity to copy data from text-delimited files in an Azure Data Lake Storage Gen2 account to a nonpartitioned table in a dedicated SQL pool of WS2 You need to configure P1 and P2 to maximize parallelism and performance.
Which dataset settings should you configure for the copy activity if each pipeline? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/load-data-overview

NEW QUESTION # 68
You haw an Azure data factory named ADF1.
You currently publish all pipeline authoring changes directly to ADF1.
You need to implement version control for the changes made to pipeline artifacts. The solution must ensure that you can apply version control to the resources currently defined m the UX Authoring canvas for ADF1.
Which two actions should you perform? Each correct answer presents part of the solution NOTE: Each correct selection is worth one point.

A. From the UX Authoring canvas, run Publish All.
B. Create a GitHub action
C. From the UX Authoring canvas, select Publish
D. Create a Git repository
E. From the UX Authoring canvas, select Set up code repository
F. Create an Azure Data Factory trigger

Answer: A,D

Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/source-control

NEW QUESTION # 69
You have an Azure Data Lake Storage Gen2 account named account1 that stores logs as shown in the following table.

You do not expect that the logs will be accessed during the retention periods.
You need to recommend a solution for account1 that meets the following requirements:
Automatically deletes the logs at the end of each retention period
Minimizes storage costs
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/access-tiers-overview

NEW QUESTION # 70
You have a SQL pool in Azure Synapse.
You discover that some queries fail or take a long time to complete.
You need to monitor for transactions that have rolled back.
Which dynamic management view should you query?

A. sys.dm_pdw_nodes_tran_database_transactions
B. sys.dm_pdw_request_steps
C. sys.dm_pdw_exec_sessions
D. sys.dm_pdw_waits

Answer: A

Explanation:
Explanation
You can use Dynamic Management Views (DMVs) to monitor your workload including investigating query execution in SQL pool.
If your queries are failing or taking a long time to proceed, you can check and monitor if you have any transactions rolling back.
Example:
-- Monitor rollback
SELECT
SUM(CASE WHEN t.database_transaction_next_undo_lsn IS NOT NULL THEN 1 ELSE 0 END), t.pdw_node_id, nod.[type] FROM sys.dm_pdw_nodes_tran_database_transactions t JOIN sys.dm_pdw_nodes nod ON t.pdw_node_id = nod.pdw_node_id GROUP BY t.pdw_node_id, nod.[type] Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-manage-monit

NEW QUESTION # 71
......

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