Microsoft DP-200 Exam Questions (Updated 2021) 100% Real Question Answers

Pass Microsoft DP-200 Exam Quickly With BraindumpsIT

Who should take the DP-200 exam

The Implementing an Azure Data Solution (beta) DP-200 Exam certification is an internationally-recognized validation that identifies persons who earn it as possessing skilled as a Microsoft Certified Azure Data Engineer Associate. If candidates want significant improvement in career growth needs enhanced knowledge, skills, and talents. Implementing an Azure Data Solution (beta) DP-200 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass Implementing an Azure Data Solution (beta) DP-200 Exam then he should take this exam.

 

NEW QUESTION 43
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure SQL database named DB1 that contains a table named Table1. Table1 has a field named Customer_ID that is varchar(22).
You need to implement masking for the Customer_ID field to meet the following requirements:
* The first two prefix characters must be exposed.
* The last four prefix characters must be exposed.
* All other characters must be masked.
Solution: You implement data masking and use a credit card function mask.
Does this meet the goal?

• A. No
• B. Yes

Answer: A

 

NEW QUESTION 44
Which two metrics should you use to identify the appropriate RU/s for the telemetry data? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A. Number of requests exceeded capacity
• B. Number of requests
• C. Data + Index storage consumed
• D. Avg Troughput/s
• E. Session consistency
• F. End to end observed read latency at the 99th percentile

Answer: B,C

Explanation:
Scenario: The telemetry data must be monitored for performance issues. You must adjust the Cosmos DB Request Units per second (RU/s) to maintain a performance SLA while minimizing the cost of the Ru/s.
With Azure Cosmos DB, you pay for the throughput you provision and the storage you consume on an hourly basis.
While you estimate the number of RUs per second to provision, consider the following factors:
Item size: As the size of an item increases, the number of RUs consumed to read or write the item also increases.
Topic 4, ADatum Corporation
Existing Environment
ADatum has one database server that has Microsoft SQL Server 2016 installed. The server hosts three mission-critical databases named SALESDB, DOCDB, and REPORTINGDB.
SALESDB collects data from the stored and the website.
DOCDB stored documents that connect to the sales data in SALESDB. The documents are stored in two different JSON formats based on the sales channel.
REPORTINGDB stores reporting data and contains server columnstore indexes. A daily process creates reporting data in REPORTINGDB from the data in SALESDB. The process is implemented as a SQL Server Integration Services (SSIS) package that runs a stored procedure from SALESDB.
Requirements
Planned Changes
ADatum plans to move the current data infrastructure to Azure. The new infrastructure has the following requirements:
Migrate SALESDB and REPORTINGDB to an Azure SQL database.
Migrate DOCDB to Azure Cosmos DB.
The sales data including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytic process will perform aggregations that must be done continuously, without gaps, and without overlapping.
As they arrive, all the sales documents in JSON format must be transformed into one consistent format.
Azure Data Factory will replace the SSIS process of copying the data from SALESDB to REPORTINGDB.
Technical Requirements
The new Azure data infrastructure must meet the following technical requirements:
Data in SALESDB must encrypted by using Transparent Data Encryption (TDE). The encryption must use your own key.
SALESDB must be restorable to any given minute within the past three weeks.
Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.
Missing indexes must be created automatically for REPORTINGDB.
Disk IO, CPU, and memory usage must be monitored for SALESDB.

 

NEW QUESTION 45
You develop data engineering solutions for a company.
You need to deploy a Microsoft Azure Stream Analytics job for an IoT solution. The solution must:
* Minimize latency.
* Minimize bandwidth usage between the job and IoT device.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

 

NEW QUESTION 46
You manage security for a database that supports a line of business application.
Private and personal data stored in the database must be protected and encrypted.
You need to configure the database to use Transparent Data Encryption (TDE).
Which five actions should you perform in sequence? To answer, select the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation

Step 1: Create a master key
Step 2: Create or obtain a certificate protected by the master key
Step 3: Set the context to the company database
Step 4: Create a database encryption key and protect it by the certificate Step 5: Set the database to use encryption Example code:
USE master;
GO
CREATE MASTER KEY ENCRYPTION BY PASSWORD = '<UseStrongPasswordHere>';
go
CREATE CERTIFICATE MyServerCert WITH SUBJECT = 'My DEK Certificate';
go
USE AdventureWorks2012;
GO
CREATE DATABASE ENCRYPTION KEY
WITH ALGORITHM = AES_128
ENCRYPTION BY SERVER CERTIFICATE MyServerCert;
GO
ALTER DATABASE AdventureWorks2012
SET ENCRYPTION ON;
GO
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption

 

NEW QUESTION 47
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
A workload for data engineers who will use Python and SQL
A workload for jobs that will run notebooks that use Python, Spark, Scala, and SQL A workload that data scientists will use to perform ad hoc analysis in Scala and R The enterprise architecture team at your company identifies the following standards for Databricks environments:
The data engineers must share a cluster.
The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databrick clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a High Concurrency cluster for the jobs.
Does this meet the goal?

• A. No
• B. Yes

Answer: B

Explanation:
Explanation
We need a High Concurrency cluster for the data engineers and the jobs.
Note:
Standard clusters are recommended for a single user. Standard can run workloads developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
References:
https://docs.azuredatabricks.net/clusters/configure.html

 

NEW QUESTION 48
You are developing the data platform for a global retail company. The company operates during normal working hours in each region. The analytical database is used once a week for building sales projections.
Each region maintains its own private virtual network.
Building the sales projections is very resource intensive are generates upwards of 20 terabytes (TB) of data.
Microsoft Azure SQL Databases must be provisioned.
Database provisioning must maximize performance and minimize cost
The daily sales for each region must be stored in an Azure SQL Database instance Once a day, the data for all regions must be loaded in an analytical Azure SQL Database instance You need to provision Azure SQL database instances.
How should you provision the database instances? To answer, drag the appropriate Azure SQL products to the correct databases. Each Azure SQL product 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: Azure SQL Database elastic pools
SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands. The databases in an elastic pool are on a single Azure SQL Database server and share a set number of resources at a set price. Elastic pools in Azure SQL Database enable SaaS developers to optimize the price performance for a group of databases within a prescribed budget while delivering performance elasticity for each database.
Box 2: Azure SQL Database Hyperscale
A Hyperscale database is an Azure SQL database in the Hyperscale service tier that is backed by the Hyperscale scale-out storage technology. A Hyperscale database supports up to 100 TB of data and provides high throughput and performance, as well as rapid scaling to adapt to the workload requirements. Scaling is transparent to the application - connectivity, query processing, and so on, work like any other SQL database.

 

NEW QUESTION 49
You are implementing automatic tuning mode for Azure SQL databases.
Automatic tuning is configured as shown in the following table.

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:

Automatic tuning options can be independently enabled or disabled per database, or they can be configured on SQL Database servers and applied on every database that inherits settings from the server. SQL Database servers can inherit Azure defaults for Automatic tuning settings. Azure defaults at this time are set to FORCE_LAST_GOOD_PLAN is enabled, CREATE_INDEX is enabled, and DROP_INDEX is disabled.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-automatic-tuning

 

NEW QUESTION 50
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 toad 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 an external file format and external table using the external data source
3. Load the data using the INSERT...SELECT statement
Does the solution meet the goal?

• A. No
• B. Yes

Answer: A

Explanation:
Explanation
You 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

 

NEW QUESTION 51
You manage a financial computation data analysis process. Microsoft Azure virtual machines (VMs) run the process in daily jobs, and store the results in virtual hard drives (VHDs.) The VMs product results using data from the previous day and store the results in a snapshot of the VHD.
When a new month begins, a process creates a new VHD.
You must implement the following data retention requirements:
* Daily results must be kept for 90 days
* Data for the current year must be available for weekly reports
* Data from the previous 10 years must be stored for auditing purposes
* Data required for an audit must be produced within 10 days of a request.
You need to enforce the data retention requirements while minimizing cost.
How should you configure the lifecycle policy? To answer, drag the appropriate JSON segments to the correct locations. Each JSON segment may be used once, more than once, or not at all. You may need to drag the split bat between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

The Set-AzStorageAccountManagementPolicy cmdlet creates or modifies the management policy of an Azure Storage account.
Example: Create or update the management policy of a Storage account with ManagementPolicy rule objects.
Action -BaseBlobAction Delete -daysAfterModificationGreaterThan 100
PS C:\>$action1 = Add-AzStorageAccountManagementPolicyAction -InputObject $action1 -BaseBlobAction TierToArchive -daysAfterModificationGreaterThan 50 PS C:\>$action1 = Add-AzStorageAccountManagementPolicyAction -InputObject $action1 -BaseBlobAction TierToCool -daysAfterModificationGreaterThan 30 PS C:\>$action1 = Add-AzStorageAccountManagementPolicyAction -InputObject $action1 -SnapshotAction Delete -daysAfterCreationGreaterThan 100 PS C:\>$filter1 = New-AzStorageAccountManagementPolicyFilter -PrefixMatch ab,cd PS C:\>$rule1 = New-AzStorageAccountManagementPolicyRule -Name Test -Action $action1 -Filter $filter1 PS C:\>$action2 = Add-AzStorageAccountManagementPolicyAction -BaseBlobAction Delete
-daysAfterModificationGreaterThan 100
PS C:\>$filter2 = New-AzStorageAccountManagementPolicyFilter
References:
https://docs.microsoft.com/en-us/powershell/module/az.storage/set-azstorageaccountmanagementpolicy

 

NEW QUESTION 52
Which counter should you monitor for real-time processing to meet the technical requirements?

• A. SU% Utilization
• B. Concurrent users
• C. Data Conversion Errors

Answer: A

Explanation:
Explanation
Scenario:
Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.
The sales data including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics.
Streaming Units (SUs) represents the computing resources that are allocated to execute a Stream Analytics job. The higher the number of SUs, the more CPU and memory resources are allocated for your job. This capacity lets you focus on the query logic and abstracts the need to manage the hardware to run your Stream Analytics job in a timely manner.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption

 

NEW QUESTION 53
You are the data engineer tor your company. An application uses a NoSQL database to store data. The database uses the key-value and wide-column NoSQL database type.
Developers need to access data in the database using an API.
You need to determine which API to use for the database model and type.
Which two APIs should you use? Each correct answer presents a complete solution.
NOTE: Each correct selection s worth one point.

• A. Cassandra API
• B. Gremlin API
• C. MongoDB API
• D. Table API
• E. SQL API

Answer: A,C

Explanation:
B: Azure Cosmos DB is the globally distributed, multimodel database service from Microsoft for mission-critical applications. It is a multimodel database and supports document, key-value, graph, and columnar data models.
E: Wide-column stores store data together as columns instead of rows and are optimized for queries over large datasets. The most popular are Cassandra and HBase.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/graph-introduction
https://www.mongodb.com/scale/types-of-nosql-databases

 

NEW QUESTION 54
A company is planning to use Microsoft Azure Cosmos DB as the data store for an application. You have the following Azure CLI command:
az cosmosdb create --name "cosmosdbdev1" --resource-group "rgdev"
You need to minimize latency and expose the SQL API. How should you complete the command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Eventual
With Azure Cosmos DB, developers can choose from five well-defined consistency models on the consistency spectrum. From strongest to more relaxed, the models include strong, bounded staleness, session, consistent prefix, and eventual consistency.
The following image shows the different consistency levels as a spectrum.

Box 2: GlobalDocumentDB
Select Core(SQL) to create a document database and query by using SQL syntax.
Note: The API determines the type of account to create. Azure Cosmos DB provides five APIs: Core(SQL) and MongoDB for document databases, Gremlin for graph databases, Azure Table, and Cassandra.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels
https://docs.microsoft.com/en-us/azure/cosmos-db/create-sql-api-dotnet

 

NEW QUESTION 55
You develop data engineering solutions for a company.
A project requires an in-memory batch data processing solution.
You need to provision an HDInsight cluster for batch processing of data on Microsoft Azure.
How should you complete the PowerShell segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-jupyter-spark-sql-use-powershell
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-overview

 

NEW QUESTION 56
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.

Answer:

Explanation:
See the explanation below.
Explanation
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.
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/sql-database/sql-database-elastic-pool-failover-group-tutorial

 

NEW QUESTION 57
You need to ensure phone-based polling data upload reliability requirements are met. How should you configure monitoring? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

References:
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/metrics-supported

 

NEW QUESTION 58
Your company manages on-premises Microsoft SQL Server pipelines by using a custom solution.
The data engineering team must implement a process to pull data from SQL Server and migrate it to Azure Blob storage. The process must orchestrate and manage the data lifecycle.
You need to configure Azure Data Factory to connect to the on-premises SQL Server database.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation

Step 1: Create a virtual private network (VPN) connection from on-premises to Microsoft Azure.
You can also use IPSec VPN or Azure ExpressRoute to further secure the communication channel between your on-premises network and Azure.
Azure Virtual Network is a logical representation of your network in the cloud. You can connect an on-premises network to your virtual network by setting up IPSec VPN (site-to-site) or ExpressRoute (private peering).
Step 2: Create an Azure Data Factory resource.
Step 3: Configure a self-hosted integration runtime.
You create a self-hosted integration runtime and associate it with an on-premises machine with the SQL Server database. The self-hosted integration runtime is the component that copies data from the SQL Server database on your machine to Azure Blob storage.
Note: A self-hosted integration runtime can run copy activities between a cloud data store and a data store in a private network, and it can dispatch transform activities against compute resources in an on-premises network or an Azure virtual network. The installation of a self-hosted integration runtime needs on an on-premises machine or a virtual machine (VM) inside a private network.
References:
https://docs.microsoft.com/en-us/azure/data-factory/tutorial-hybrid-copy-powershell

 

NEW QUESTION 59
Your company uses Azure SQL Database and Azure Blob storage.
All data at rest must be encrypted by using the company's own key. The solution must minimize administrative effort and the impact to applications which use the database.
You need to configure security.
What should you implement? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

 

NEW QUESTION 60
You plan to create a dimension table in Azure Data Warehouse that will be less than 1 GB.
You need to create the table to meet the following requirements:
Provide the fastest query time.
Minimize data movement.
Which type of table should you use?

• A. replicated
• B. heap
• C. round-robin
• D. hash distributed

Answer: A

Explanation:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/design-guidance-for-replicated-tables

 

NEW QUESTION 61
You need to process and query ingested Tier 9 data.
Which two options should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A. Azure Cache for Redis
• B. Azure Notification Hub
• C. Apache Kafka statements
• D. Azure Stream Analytics
• E. Azure Event Grid
• F. Transact-SQL statements

Answer: D,E

Explanation:
Event Hubs provides a Kafka endpoint that can be used by your existing Kafka based applications as an alternative to running your own Kafka cluster.
You can stream data into Kafka-enabled Event Hubs and process it with Azure Stream Analytics, in the following steps:
Create a Kafka enabled Event Hubs namespace.
Create a Kafka client that sends messages to the event hub.
Create a Stream Analytics job that copies data from the event hub into an Azure blob storage.
Scenario:

Tier 9 reporting must be moved to Event Hubs, queried, and persisted in the same Azure region as the company's main office
References:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-kafka-stream-analytics

 

NEW QUESTION 62
You need to ensure that phone-based polling data can be analyzed in the PollingData database.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer are and arrange them in the correct order.

Answer:

Explanation:

Explanation

Scenario:
All deployments must be performed by using Azure DevOps. Deployments must use templates used in multiple environments No credentials or secrets should be used during deployments

 

NEW QUESTION 63
Your company analyzes images from security cameras and sends to security teams that respond to unusual activity. The solution uses Azure Databricks.
You need to send Apache Spark level events, Spark Structured Streaming metrics, and application metrics to Azure Monitor.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions in the answer area and arrange them in the correct order.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/bs-latn-ba/azure/architecture/databricks-monitoring/application-logs

 

NEW QUESTION 64
You use Azure Stream Analytics to receive Twitter data from Azure Event Hubs and to output the data to an Azure Blob storage account.
You need to output the count of tweets during the last five minutes every five minutes. Each tweet must only be counted once.
Which windowing function should you use?

• A. a five-minute Session window
• B. a five-minute Tumbling window
• C. a five-minute Hopping window that has one-minute hop
• D. a five-minute Sliding window

Answer: B

Explanation:
Explanation
Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions

 

NEW QUESTION 65
......

Real Microsoft DP-200 Exam Questions [Updated 2021]: https://www.braindumpsit.com/DP-200_real-exam.html