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DP-203 Exam Discount | Valid DP-203 Test Guide

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The DP-203 certification exam consists of various topics, including designing and implementing data storage solutions on Microsoft Azure, designing and implementing data processing solutions on Microsoft Azure, and designing and implementing data integration solutions on Microsoft Azure. These topics cover various aspects of data engineering and require individuals to have a deep understanding of Microsoft Azure services and tools. DP-203 exam also requires individuals to have hands-on experience with Microsoft Azure services, as well as a strong understanding of data processing and data integration techniques.

The DP-203 Exam focuses on various topics, including data storage solutions, data processing solutions, data monitoring and optimization, and implementing security and privacy measures in data solutions. Candidates who pass DP-203 exam will prove their proficiency in designing and implementing data solutions, integrating data solutions with other services and tools, and implementing data security and privacy measures.

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To prepare for the DP-203 certification exam, candidates must have a solid understanding of Azure data technologies, including Azure Data Factory, Azure Databricks, Azure Stream Analytics, and Azure Synapse Analytics. Candidates must also have experience in designing, building, and maintaining data processing systems. Microsoft offers a variety of resources to help candidates prepare for the DP-203 Certification Exam, including online training courses, practice tests, and study guides.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q197-Q202):

NEW QUESTION # 197
You are designing an application that will store petabytes of medical imaging data When the data is first created, the data will be accessed frequently during the first week. After one month, the data must be accessible within 30 seconds, but files will be accessed infrequently. After one year, the data will be accessed infrequently but must be accessible within five minutes.
You need to select a storage strategy for the data. The solution must minimize costs.
Which storage tier should you use for each time frame? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

First week: Hot
Hot - Optimized for storing data that is accessed frequently.
After one month: Cool
Cool - Optimized for storing data that is infrequently accessed and stored for at least 30 days.
After one year: Cool

NEW QUESTION # 198
You have an enterprise data warehouse in Azure Synapse Analytics that contains a table named FactOnlineSales. The table contains data from the start of 2009 to the end of 2012.
You need to improve the performance of queries against FactOnlineSales by using table partitions. The solution must meet the following requirements:
* Create four partitions based on the order date.
* Ensure that each partition contains all the orders places during a given calendar year.
How should you complete the T-SQL command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation
Text Description automatically generated

Range Left or Right, both are creating similar partition but there is difference in comparison For example: in this scenario, when you use LEFT and 20100101,20110101,20120101 Partition will be, datecol<=20100101, datecol>20100101 and datecol<=20110101, datecol>20110101 and datecol<=20120101, datecol>20120101 But if you use range RIGHT and 20100101,20110101,20120101 Partition will be, datecol<20100101, datecol>=20100101 and datecol<20110101, datecol>=20110101 and datecol<20120101, datecol>=20120101 In this example, Range RIGHT will be suitable for calendar comparison Jan 1st to Dec 31st Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-partition-function-transact-sql?view=sql-server-ver1

NEW QUESTION # 199
You have the following Azure Stream Analytics query.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Yes
You can now use a new extension of Azure Stream Analytics SQL to specify the number of partitions of a stream when reshuffling the data.
The outcome is a stream that has the same partition scheme. Please see below for an example:
WITH step1 AS (SELECT * FROM [input1] PARTITION BY DeviceID INTO 10),
step2 AS (SELECT * FROM [input2] PARTITION BY DeviceID INTO 10)
SELECT * INTO [output] FROM step1 PARTITION BY DeviceID UNION step2 PARTITION BY DeviceID Note: The new extension of Azure Stream Analytics SQL includes a keyword INTO that allows you to specify the number of partitions for a stream when performing reshuffling using a PARTITION BY statement.
Box 2: Yes
When joining two streams of data explicitly repartitioned, these streams must have the same partition key and partition count.
Box 3: Yes
10 partitions x six SUs = 60 SUs is fine.
Note: Remember, Streaming Unit (SU) count, which is the unit of scale for Azure Stream Analytics, must be adjusted so the number of physical resources available to the job can fit the partitioned flow. In general, six SUs is a good number to assign to each partition. In case there are insufficient resources assigned to the job, the system will only apply the repartition if it benefits the job.
Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/

NEW QUESTION # 200
You are designing an application that will use an Azure Data Lake Storage Gen 2 account to store petabytes of license plate photos from toll booths. The account will use zone-redundant storage (ZRS).
You identify the following usage patterns:
* The data will be accessed several times a day during the first 30 days after the data is created. The data must meet an availability SU of 99.9%.
* After 90 days, the data will be accessed infrequently but must be available within 30 seconds.
* After 365 days, the data will be accessed infrequently but must be available within five minutes.

Answer:

Explanation:

Explanation:
Box 1: Hot
The data will be accessed several times a day during the first 30 days after the data is created. The data must meet an availability SLA of 99.9%.
Box 2: Cool
After 90 days, the data will be accessed infrequently but must be available within 30 seconds.
Data in the Cool tier should be stored for a minimum of 30 days.
When your data is stored in an online access tier (either Hot or Cool), users can access it immediately. The Hot tier is the best choice for data that is in active use, while the Cool tier is ideal for data that is accessed less frequently, but that still must be available for reading and writing.
Box 3: Cool
After 365 days, the data will be accessed infrequently but must be available within five minutes.
Reference: https://docs.microsoft.com/en-us/azure/storage/blobs/access-tiers-overview
https://docs.microsoft.com/en-us/azure/storage/blobs/archive-rehydrate-overview

NEW QUESTION # 201
You plan to implement an Azure Data Lake Gen2 storage account.
You need to ensure that the data lake will remain available if a data center fails in the primary Azure region.
The solution must minimize costs.
Which type of replication should you use for the storage account?

A. zone-redundant storage (ZRS)
B. geo-redundant storage (GRS)
C. locally-redundant storage (LRS)
D. geo-zone-redundant storage (GZRS)

Answer: B

NEW QUESTION # 202
......

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