DP-203 Questions & New DP-203 Exam Testking
DP-203 Questions & New DP-203 Exam Testking
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Microsoft DP-203 certification exam is designed to test your skills and knowledge in data engineering on the Microsoft Azure platform. Data Engineering on Microsoft Azure certification is ideal for data engineers who want to leverage Azure data services to design and implement scalable data solutions. DP-203 Exam measures your ability to design and implement data storage solutions, manage data processing, and monitor and optimize data solutions.
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Many customers may doubt the quality of our Microsoft DP-203 learning quiz since they haven't tried them. But our DP-203 training engine is reliable. What you have learnt on our Data Engineering on Microsoft Azure DP-203 Exam Materials are going through special selection. The core knowledge of the real exam is significant.
Microsoft DP-203 (Data Engineering on Microsoft Azure) certification is a highly sought-after accreditation for data engineers who want to demonstrate their knowledge and skills in designing and implementing data solutions on the Azure platform. Data Engineering on Microsoft Azure certification validates a candidate's technical expertise in building data processing systems, data storage solutions, and data transformation and integration solutions using Azure services.
To take the DP-203 exam, you should have a solid understanding of data processing technologies, data storage options, data security and compliance, and data integration and transformation techniques. You should also be familiar with Azure services such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Stream Analytics. By passing DP-203 Exam, you can prove your ability to work with Azure tools and technologies, and showcase your expertise in data engineering on the Microsoft Azure platform.
Microsoft Data Engineering on Microsoft Azure Sample Questions (Q162-Q167):
NEW QUESTION # 162
You have an on-premises data warehouse that includes the following fact tables. Both tables have the following columns: DateKey, ProductKey, RegionKey. There are 120 unique product keys and 65 unique region keys.
Queries that use the data warehouse take a long time to complete.
You plan to migrate the solution to use Azure Synapse Analytics. You need to ensure that the Azure-based solution optimizes query performance and minimizes processing skew.
What should you recommend? 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/sql-data-warehouse/sql-data-warehouse-tables-distribute
NEW QUESTION # 163
You have an Azure event hub named retailhub that has 16 partitions. Transactions are posted to retailhub. Each transaction includes the transaction ID, the individual line items, and the payment details. The transaction ID is used as the partition key.
You are designing an Azure Stream Analytics job to identify potentially fraudulent transactions at a retail store. The job will use retailhub as the input. The job will output the transaction ID, the individual line items, the payment details, a fraud score, and a fraud indicator.
You plan to send the output to an Azure event hub named fraudhub.
You need to ensure that the fraud detection solution is highly scalable and processes transactions as quickly as possible.
How should you structure the output of the Stream Analytics job? 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/event-hubs/event-hubs-features#partitions
NEW QUESTION # 164
You have an Azure Synapse Analytics dedicated SQL pool.
You need to monitor the database for long-running queries and identify which queries are waiting on resources Which dynamic management view should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE; Each correct answer is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 165
You have an Azure subscription that contains an Azure Data Lake Storage account. The storage account contains a data lake named DataLake1.
You plan to use an Azure data factory to ingest data from a folder in DataLake1, transform the data, and land the data in another folder.
You need to ensure that the data factory can read and write data from any folder in the DataLake1 file system. The solution must meet the following requirements:
Minimize the risk of unauthorized user access.
Use the principle of least privilege.
Minimize maintenance effort.
How should you configure access to the storage account for the data factory? 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/active-directory/managed-identities-azure-resources/overview
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-data-lake-storage
NEW QUESTION # 166
You are building an Azure Data Factory solution to process data received from Azure Event Hubs, and then ingested into an Azure Data Lake Storage Gen2 container.
The data will be ingested every five minutes from devices into JSON files. The files have the following naming pattern.
/{deviceType}/in/{YYYY}/{MM}/{DD}/{HH}/{deviceID}_{YYYY}{MM}{DD}HH}{mm}.json You need to prepare the data for batch data processing so that there is one dataset per hour per deviceType.
The solution must minimize read times.
How should you configure the sink for the copy activity? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: @trigger().startTime
startTime: A date-time value. For basic schedules, the value of the startTime property applies to the first occurrence. For complex schedules, the trigger starts no sooner than the specified startTime value.
Box 2: /{YYYY}/{MM}/{DD}/{HH}_{deviceType}.json
One dataset per hour per deviceType.
Box 3: Flatten hierarchy
- FlattenHierarchy: All files from the source folder are in the first level of the target folder. The target files have autogenerated names.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipeline-execution-triggers
https://docs.microsoft.com/en-us/azure/data-factory/connector-file-system
NEW QUESTION # 167
......
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