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Detailed DP-203 Answers | New DP-203 Exam Objectives

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Microsoft DP-203 exam is a challenging exam that requires in-depth knowledge of data engineering on the Azure platform. Candidates are expected to have a solid understanding of data engineering concepts, including data modeling, data ingestion, data processing, and data analysis. They should also be familiar with Azure data services, including Azure SQL Database, Azure SQL Managed Instance, Azure HDInsight, and Azure Data Lake Analytics.

Microsoft DP-203 (Data Engineering on Microsoft Azure) Certification Exam is designed to test an individual's knowledge and skills in data engineering using Microsoft Azure. Data Engineering on Microsoft Azure certification is ideal for individuals who work with data and have experience with Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, and Azure Stream Analytics. DP-203 Exam is intended to validate the candidate's ability to design, implement, and maintain data processing solutions using Microsoft's cloud platform.

>> Detailed DP-203 Answers <<

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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q304-Q309):

NEW QUESTION # 304
You develop a dataset named DBTBL1 by using Azure Databricks.
DBTBL1 contains the following columns:
SensorTypeID
GeographyRegionID
Year
Month
Day
Hour
Minute
Temperature
WindSpeed
Other
You need to store the data to support daily incremental load pipelines that vary for each GeographyRegionID. The solution must minimize storage costs.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 305
You are incrementally loading data into fact tables in an Azure Synapse Analytics dedicated SQL pool.
Each batch of incoming data is staged before being loaded into the fact tables. | You need to ensure that the incoming data is staged as quickly as possible. | How should you configure the staging tables? To answer, select the appropriate options in the answer area.

Answer:

Explanation:

Explanation

Round-robin distribution is recommended for staging tables because it distributes data evenly across all the distributions without requiring a hash column. This can improve the speed of data loading and avoid data skew. Heap tables are recommended for staging tables because they do not have any indexes or partitions that can slow down the data loading process. Heap tables are also easier to truncate and reload than clustered index or columnstore index tables.

NEW QUESTION # 306
You plan to create a table in an Azure Synapse Analytics dedicated SQL pool.
Data in the table will be retained for five years. Once a year, data that is older than five years will be deleted.
You need to ensure that the data is distributed evenly across partitions. The solution must minimize the amount of time required to delete old data.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: HASH
Box 2: OrderDateKey
In most cases, table partitions are created on a date column.
A way to eliminate rollbacks is to use Metadata Only operations like partition switching for data management.
For example, rather than execute a DELETE statement to delete all rows in a table where the order_date was in October of 2001, you could partition your data early. Then you can switch out the partition with data for an empty partition from another table.
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/best-practices-dedicated-sql-pool

NEW QUESTION # 307
You have an Azure Databricks workspace named workspace! in the Standard pricing tier. Workspace1 contains an all-purpose cluster named cluster1.
You need to reduce the time it takes for cluster 1 to start and scale up. The solution must minimize costs.
What should you do first?

A. Configure a global init script for workspace1.
B. Create a pool in workspace1.
C. Upgrade workspace1 to the Premium pricing tier.
D. Create a cluster policy in workspace1.

Answer: B

Explanation:
You can use Databricks Pools to Speed up your Data Pipelines and Scale Clusters Quickly.
Databricks Pools, a managed cache of virtual machine instances that enables clusters to start and scale 4 times faster.
Reference:
https://databricks.com/blog/2019/11/11/databricks-pools-speed-up-data-pipelines.html

NEW QUESTION # 308
You plan to create an Azure Data Lake Storage Gen2 account
You need to recommend a storage solution that meets the following requirements:
* Provides the highest degree of data resiliency
* Ensures that content remains available for writes if a primary data center fails What should you include in the recommendation? To answer, select the appropriate options in the answer area.

Answer:

Explanation:

https://docs.microsoft.com/en-us/azure/storage/common/storage-disaster-recovery-guidance?toc=/azure/storage/blobs/toc.json
https://docs.microsoft.com/en-us/answers/questions/32583/azure-data-lake-gen2-disaster-recoverystorage-acco.html

NEW QUESTION # 309
......

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