DP-203Data Engineering on Microsoft Azure
380 Questions and Answers Experienced specialists selected 380 questions for this exam. All answers are verified to ensure correctness.
Last Updated Apr 25, 2024 Ace your exams with our consistently updated DP-203 exam dumps.
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DP-203 Online Practice Questions and Answers
HOTSPOT
You have an Azure Storage account that generates 200.000 new files daily. The file names have a format of (YYY)/(MM)/(DD)/|HH])/(CustornerID).csv.
You need to design an Azure Data Factory solution that will toad new data from the storage account to an Azure Data lake once hourly. The solution must minimize load times and costs.
How should you configure the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
You are implementing a batch dataset in the Parquet format.
Data tiles will be produced by using Azure Data Factory and stored in Azure Data Lake Storage Gen2. The files will be consumed by an Azure Synapse Analytics serverless SQL pool.
You need to minimize storage costs for the solution.
What should you do?
A. Store all the data as strings in the Parquet tiles.
B. Use OPENROWEST to query the Parquet files.
C. Create an external table mat contains a subset of columns from the Parquet files.
D. Use Snappy compression for the files.
You have an Azure subscription that contains an Azure Data Lake Storage account named myaccount1. The myaccount1 account contains two containers named container1 and contained. The subscription is linked to an Azure Active Directory (Azure AD) tenant that contains a security group named Group1.
You need to grant Group1 read access to contamer1. The solution must use the principle of least privilege. Which role should you assign to Group1?
A. Storage Blob Data Reader for container1
B. Storage Table Data Reader for container1
C. Storage Blob Data Reader for myaccount1
D. Storage Table Data Reader for myaccount1
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Microsoft DP-203 exam official information: As a candidate for this exam, you should have subject matter expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions.
