Microsoft DP-200 Exam Questions Instant Access

Question 1

Use the following login credentials as needed:

Azure Username: xxxxx

Azure Password: xxxxx

The following information is for technical support purposes only:

Lab Instance: 10277521

You plan to query db3 to retrieve a list of sales customers. The query will retrieve several columns that include the email address of each sales customer.

You need to modify db3 to ensure that a portion of the email addresses is hidden in the query results.

To complete this task, sign in to the Azure portal.

AExplanation:
1. Launch the Azure portal.
2. Navigate to the settings page of the database db3 that includes the sensitive data you want to mask.
3. Click the Dynamic Data Masking tile that launches the Dynamic Data Masking configuration page.
Note: Alternatively, you can scroll down to the Operations section and click Dynamic Data Masking.

4. In the Dynamic Data Masking configuration page, you may see some database columns that the recommendations engine has flagged for masking.

5. Click ADD MASK for the EmailAddress column
6. Click Save in the data masking rule page to update the set of masking rules in the dynamic data masking policy.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-dynamic-data-masking-get-started-portal

Answer : A

Question 2

You need to develop a pipeline for processing dat

a. The pipeline must meet the following requirements.

*Scale up and down resources for cost reduction.

*Use an in-memory data processing engine to speed up ETL and machine learning operations.

*Use streaming capabilities.

*Provide the ability to code in SQL, Python, Scala, and R.

*Integrate workspace collaboration with Git.

What should you use?

AHDInsight Spark Cluster

BAzure Stream Analytics

CHDInsight Hadoop Cluster

DAzure SQL Data Warehouse

Answer : A

Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.

HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.

Languages: R, Python, Java, Scala, SQL

You can create an HDInsight Spark cluster using an Azure Resource Manager template. The template can be found in GitHub.

References:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing

Question 3

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.

You develop a data ingestion process that will import data to a Microsoft Azure SQL Data Warehouse.

The data to be ingested resides in parquet files stored in an Azure Data lake Gen 2 storage account.

You need to load the data from the Azure Data Lake Gen 2 storage account into the Azure SQL Data Warehouse.

Solution:

1. Create an external data source pointing to the Azure storage account

2. Create a workload group using the Azure storage account name as the pool name

3. Load the data using the INSERT...SELECT statement

Does the solution meet the goal?

AYes

BNo

Answer : B

You need to create an external file format and external table using the external data source.

You then load the data using the CREATE TABLE AS SELECT statement.

References:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure-data-lake-store

Question 4

Use the following login credentials as needed:

Azure Username: xxxxx

Azure Password: xxxxx

The following information is for technical support purposes only:

Lab Instance: 10543936

You need to create an elastic pool that contains an Azure SQL database named db2 and a new SQL database named db3.

To complete this task, sign in to the Azure portal.

AExplanation:
Step 1: Create a new SQL database named db3
1. Select SQL in the left-hand menu of the Azure portal. If SQL is not in the list, select All services, then type SQL in the search box.
2. Select + Add to open the Select SQL deployment option page. Select Single Database. You can view additional information about the different databases by selecting Show details on the Databases tile.
3. Select Create:

4. Enter the required fields if necessary.
5. Leave the rest of the values as default and select Review + Create at the bottom of the form.
6. Review the final settings and select Create. Use Db3 as database name.
On the SQL Database form, select Create to deploy and provision the resource group, server, and database.
Step 2: Create your elastic pool using the Azure portal.
1. Select Azure SQL in the left-hand menu of the Azure portal. If Azure SQL is not in the list, select All services, then type Azure SQL in the search box.
2. Select + Add to open the Select SQL deployment option page.
3. Select Elastic pool from the Resource type drop-down in the SQL Databases tile. Select Create to create your elastic pool.

4. Configure your elastic pool with the following values:
Name: Provide a unique name for your elastic pool, such as myElasticPool.
Subscription: Select your subscription from the drop-down.
ResourceGroup: Select the resource group.
Server: Select the server

5. Select Configure elastic pool
6. On the Configure page, select the Databases tab, and then choose to Add database.

7. Add the Azure SQL database named db2, and the new SQL database named db3 that you created in Step 1.
8. Select Review + create to review your elastic pool settings and then select Create to create your elastic pool.

Answer : A

https://docs.microsoft.com/bs-latn-ba/azure/sql-database/sql-database-elastic-pool-failover-group-tutorial

Question 5

You are developing a data engineering solution for a company. The solution will store a large set of key-value pair data by using Microsoft Azure Cosmos DB

The solution has the following requirements:

* Data must be partitioned into multiple containers.

* Data containers must be configured separately.

* Data must be accessible from applications hosted around the world.

* The solution must minimize latency.

You need to provision Azure Cosmos DB

AConfigure account-level throughput.

BProvision an Azure Cosmos DB account with the Azure Table API Enable geo-redundancy.

CConfigure table-level throughput

DReplicate the data globally by manually adding regions lo the Azure Cosmos DB account.

EProvision an Azure Cosmos DB account with the Azure Table API. Enable multi-region writes.

Answer : E

Scale read and write throughput globally. You can enable every region to be writable and elastically scale reads and writes all around the world. The throughput that your application configures on an Azure Cosmos database or a container is guaranteed to be delivered across all regions associated with your Azure Cosmos account. The provisioned throughput is guaranteed up by financially backed SLAs.

References:

https://docs.microsoft.com/en-us/azure/cosmos-db/distribute-data-globally

Question 6

You develop data engineering solutions for a company.

A project requires the deployment of data to Azure Data Lake Storage.

You need to implement role-based access control (RBAC) so that project members can manage the Azure Data Lake Storage resources.

Which three actions should you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

AAssign Azure AD security groups to Azure Data Lake Storage.

BConfigure end-user authentication for the Azure Data Lake Storage account.

CConfigure service-to-service authentication for the Azure Data Lake Storage account.

DCreate security groups in Azure Active Directory (Azure AD) and add project members.

EConfigure access control lists (ACL) for the Azure Data Lake Storage account.
References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-secure-data

Answer : A, D, E

Question 7

You need to set up Azure Data Factory pipelines to meet data movement requirements.

Which integration runtime should you use?

Aself-hosted integration runtime

BAzure-SSIS Integration Runtime

C.NET Common Language Runtime (CLR)

DAzure integration runtime

Answer : A

The following table describes the capabilities and network support for each of the integration runtime types:

Scenario: The solution must support migrating databases that support external and internal application to Azure SQL Database. The migrated databases will be supported by Azure Data Factory pipelines for the continued movement, migration and updating of data both in the cloud and from local core business systems and repositories.

References:

https://docs.microsoft.com/en-us/azure/data-factory/concepts-integration-runtime

Microsoft Implementing an Azure Data Solution DP-200 Exam Questions