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Microsoft DP-203 (Data Engineering on Microsoft Azure) Exam is an essential certification for data professionals who are interested in working with data engineering concepts on the Microsoft Azure platform. DP-203 exam is designed to test an individual's knowledge and understanding of Azure data services, including the Azure Data Factory, Azure Synapse Analytics, and Azure Stream Analytics. The DP-203 Certification is an excellent way to demonstrate your expertise in data engineering on Azure and showcase your ability to design and implement data solutions using Azure services.
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Candidates who become Microsoft DP-203 certified demonstrate their worth in the Microsoft field. The Data Engineering on Microsoft Azure (DP-203) certification is proof of their competence and skills. This is a highly sought-after skill in large Microsoft companies and makes a career easier for the candidate. To become certified, you must pass the Data Engineering on Microsoft Azure (DP-203) certification exam. For this task, you need high-quality and accurate Data Engineering on Microsoft Azure (DP-203) exam dumps. We have seen that candidates who study with outdated Data Engineering on Microsoft Azure (DP-203) practice material don't get success and lose their resources.
Microsoft DP-203 (Data Engineering on Microsoft Azure) certification exam is designed for professionals who want to validate their skills in designing and implementing data solutions on Microsoft Azure. Data Engineering on Microsoft Azure certification exam measures your ability to work with different Azure data services like Azure Data Factory, Azure Stream Analytics, Azure Databricks, and more. As a data engineer, you will learn how to use these tools to transform raw data into meaningful insights that can help organizations make better decisions.
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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q106-Q111):
NEW QUESTION # 106
You have an enterprise data warehouse in Azure Synapse Analytics named DW1 on a server named Server1.
You need to verify whether the size of the transaction log file for each distribution of DW1 is smaller than 160 GB.
What should you do?
Answer: C
Explanation:
D. Execute a query against the logs of DW1 by using the Get-AzOperationalInsightSearchResult PowerShell cmdlet.
Explanation:
The following query returns the transaction log size on each distribution. If one of the log files is reaching 160 GB, you should consider scaling up your instance or limiting your transaction size.
-- Transaction log size
SELECT
instance_name as distribution_db,
cntr_value*1.0/1048576 as log_file_size_used_GB,
pdw_node_id
FROM sys.dm_pdw_nodes_os_performance_counters
WHERE
instance_name like 'Distribution_%'
AND counter_name = 'Log File(s) Used Size (KB)'
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-monitor
NEW QUESTION # 107
You have two fact tables named Flight and Weather. Queries targeting the tables will be based on the join between the following columns.
You need to recommend a solution that maximum query performance.
What should you include in the recommendation?
Answer: A
NEW QUESTION # 108
You are building an Azure Stream Analytics job that queries reference data from a product catalog file. The file is updated daily.
The reference data input details for the file are shown in the Input exhibit. (Click the Input tab.)
The storage account container view is shown in the Refdata exhibit. (Click the Refdata tab.)
You need to configure the Stream Analytics job to pick up the new reference data.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, application, table Description automatically generated
Box 1: {date}/product.csv
In the 2nd exhibit we see: Location: refdata / 2020-03-20
Note: Path Pattern: This is a required property that is used to locate your blobs within the specified container.
Within the path, you may choose to specify one or more instances of the following 2 variables:
{date}, {time}
Example 1: products/{date}/{time}/product-list.csv
Example 2: products/{date}/product-list.csv
Example 3: product-list.csv
Box 2: YYYY-MM-DD
Note: Date Format [optional]: If you have used {date} within the Path Pattern that you specified, then you can select the date format in which your blobs are organized from the drop-down of supported formats.
Example: YYYY/MM/DD, MM/DD/YYYY, etc.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-use-reference-data
NEW QUESTION # 109
You store files in an Azure Data Lake Storage Gen2 container. The container has the storage policy shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection Is worth one point.
Answer:
Explanation:
NEW QUESTION # 110
You have an Azure Synapse Analytics pipeline named Pipeline1 that contains a data flow activity named Dataflow1.
Pipeline1 retrieves files from an Azure Data Lake Storage Gen 2 account named storage1.
Dataflow1 uses the AutoResolveIntegrationRuntime integration runtime configured with a core count of 128.
You need to optimize the number of cores used by Dataflow1 to accommodate the size of the files in storage1.
What should you configure? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Explanation
Box 1: A Get Metadata activity
Dynamically size data flow compute at runtime
The Core Count and Compute Type properties can be set dynamically to adjust to the size of your incoming source data at runtime. Use pipeline activities like Lookup or Get Metadata in order to find the size of the source dataset data. Then, use Add Dynamic Content in the Data Flow activity properties.
Box 2: Dynamic content
Reference: https://docs.microsoft.com/en-us/azure/data-factory/control-flow-execute-data-flow-activity
NEW QUESTION # 111
......
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