DP-200 Practice Microsoft Verified Answers - Pass Your Exams For Sure! [2021]
Valid Way To Pass Azure Data Engineer Associate's DP-200 Exam
Potential Candidates and Requirements
According to the fact that this is an associate-level certification track, there are no strict requirements that you must fulfill except passing two exams. Thus, if you are planning to take Microsoft DP-200, you can be an Azure Data Engineer who wants to verify the skills to get certified or a specialist who is just starting an IT career. In both cases, you should have a solid knowledge of the content and be able to clear the tests with high results.
A potential candidate for the Microsoft DP-200 exam should know how to identify and meet the requirements by collaborating with the business stakeholders to implement data solutions that use Azure data services. Besides that, it is required that the individuals have the relevant skills in implementing various data solutions, such as Azure Blob storage, Azure Databricks, Azure Data Factory, Azure Stream Analytics, Azure Synapse Analytics, and Azure Cosmos DB. Also, they need to be able to ingest batch and streaming data, provision data storage services, identify performance bottlenecks, implement security requirements, access external data sources, transform data, and implement data retention policies. /
Exam DP-200: Implementing an Azure Data Solution
Candidates for this exam are Microsoft Azure data engineers who collaborate with business stakeholders to identify and meet the data requirements to implement data solutions that use Azure data services.
Azure data engineers are responsible for data-related implementation tasks that include provisioning data storage services, ingesting streaming and batch data, transforming data, implementing security requirements, implementing data retention policies, identifying performance bottlenecks, and accessing external data sources.
Candidates for this exam must be able to implement data solutions that use the following Azure services: Azure Cosmos DB, Azure Synapse Analytics (formerly Azure SQL DW), Azure Data Factory, Azure Stream Analytics, Azure Databricks, and Azure Blob storage.
Part of the requirements for: Microsoft Certified: Azure Data Engineer Associate
NEW QUESTION 54
You are monitoring an Azure Stream Analytics job.
You discover that the Backlogged Input Events metric is increasing slowly and is consistently non-zero.
You need to ensure that the job can handle all the events.
What should you do?
- A. Remove any named consumer groups from the connection and use $default.
- B. Change the compatibility level of the Stream Analytics job.
- C. Create an additional output stream for the existing input stream.
- D. Increase the number of streaming units (SUs).
Answer: D
Explanation:
Explanation
Backlogged Input Events: Number of input events that are backlogged. A non-zero value for this metric implies that your job isn't able to keep up with the number of incoming events. If this value is slowly increasing or consistently non-zero, you should scale out your job. You should increase the Streaming Units.
Note: 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.
Reference:
https://docs.microsoft.com/bs-cyrl-ba/azure/stream-analytics/stream-analytics-monitoring
NEW QUESTION 55
You need to implement an Azure Databricks cluster that automatically connects to Azure Data Lake Storage Gen2 by using Azure Active Directory (Azure AD) integration.
How should you configure the new cluster? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: High Concurrency
Enable Azure Data Lake Storage credential passthrough for a high-concurrency cluster.
Incorrect:
Support for Azure Data Lake Storage credential passthrough on standard clusters is in Public Preview.
Standard clusters with credential passthrough are supported on Databricks Runtime 5.5 and above and are limited to a single user.
Box 2: Azure Data Lake Storage Gen1 Credential Passthrough
You can authenticate automatically to Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2 from Azure Databricks clusters using the same Azure Active Directory (Azure AD) identity that you use to log into Azure Databricks. When you enable your cluster for Azure Data Lake Storage credential passthrough, commands that you run on that cluster can read and write data in Azure Data Lake Storage without requiring you to configure service principal credentials for access to storage.
References:
https://docs.azuredatabricks.net/spark/latest/data-sources/azure/adls-passthrough.html
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: 10277521
You plan to create multiple pipelines in a new Azure Data Factory V2.
You need to create the data factory, and then create a scheduled trigger for the planned pipelines. The trigger must execute every two hours starting at 24:00:00.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
Step 1: Create a new Azure Data Factory V2
1. Go to the Azure portal.
2. Select Create a resource on the left menu, select Analytics, and then select Data Factory.
4. On the New data factory page, enter a name.
5. For Subscription, select your Azure subscription in which you want to create the data factory.
6. For Resource Group, use one of the following steps:
Select Use existing, and select an existing resource group from the list.
Select Create new, and enter the name of a resource group.
7. For Version, select V2.
8. For Location, select the location for the data factory.
9. Select Create.
10. After the creation is complete, you see the Data Factory page.
Step 2: Create a schedule trigger for the Data Factory
1. Select the Data Factory you created, and switch to the Edit tab.
2. Click Trigger on the menu, and click New/Edit.
3. In the Add Triggers page, click Choose trigger..., and click New.
4. In the New Trigger page, do the following steps:
a. Confirm that Schedule is selected for Type.
b. Specify the start datetime of the trigger for Start Date (UTC) to: 24:00:00 c. Specify Recurrence for the trigger. Select Every Hour, and enter 2 in the text box.
5. In the New Trigger window, check the Activated option, and click Next.
6. In the New Trigger page, review the warning message, and click Finish.
7. Click Publish to publish changes to Data Factory. Until you publish changes to Data Factory, the trigger does not start triggering the pipeline runs.
References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-schedule-trigger
NEW QUESTION 57 
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 need to create an Azure SQL database named db3 on an Azure SQL server named SQL10277521. Db3 must use the Sample (AdventureWorksLT) source.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
1. Click Create a resource in the upper left-hand corner of the Azure portal.
2. On the New page, select Databases in the Azure Marketplace section, and then click SQL Database in the Featured section.
3. Fill out the SQL Database form with the following information, as shown below:
Database name: Db3
Select source: Sample (AdventureWorksLT)
Server: SQL10277521
4. Click Select and finish the Wizard using default options.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-design-first-database
NEW QUESTION 58
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 questions sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You need to configure data encryption for external applications.
Solution:
1. Access the Always Encrypted Wizard in SQL Server Management Studio
2. Select the column to be encrypted
3. Set the encryption type to Deterministic
4. Configure the master key to use the Azure Key Vault
5. Validate configuration results and deploy the solution
Does the solution meet the goal?
- A. No
- B. Yes
Answer: B
Explanation:
Explanation
We use the Azure Key Vault, not the Windows Certificate Store, to store the master key.
Note: The Master Key Configuration page is where you set up your CMK (Column Master Key) and select the key store provider where the CMK will be stored. Currently, you can store a CMK in the Windows certificate store, Azure Key Vault, or a hardware security module (HSM).
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-always-encrypted-azure-key-vault
Topic 2, Proseware Inc
Background
Proseware, Inc, develops and manages a product named Poll Taker. The product is used for delivering public opinion polling and analysis.
Polling data comes from a variety of sources, including online surveys, house-to-house interviews, and booths at public events.
Polling data
Polling data is stored in one of the two locations:
* An on-premises Microsoft SQL Server 2019 database named PollingData
* Azure Data Lake Gen 2
Data in Data Lake is queried by using PolyBase
Poll metadata
Each poll has associated metadata with information about the poll including the date and number of respondents. The data is stored as JSON.
Phone-based polling
Security
* Phone-based poll data must only be uploaded by authorized users from authorized devices
* Contractors must not have access to any polling data other than their own
* Access to polling data must set on a per-active directory user basis
Data migration and loading
* All data migration processes must use Azure Data Factory
* All data migrations must run automatically during non-business hours
* Data migrations must be reliable and retry when needed
Performance
After six months, raw polling data should be moved to a lower-cost storage solution.
Deployments
* 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
Reliability
All services and processes must be resilient to a regional Azure outage.
Monitoring
All Azure services must be monitored by using Azure Monitor. On-premises SQL Server performance must be monitored.
NEW QUESTION 59
Each day, company plans to store hundreds of files in Azure Blob Storage and Azure Data Lake Storage.
The company uses the parquet format.
You must develop a pipeline that meets the following requirements:
Process data every six hours
Offer interactive data analysis capabilities
Offer the ability to process data using solid-state drive (SSD) caching
Use Directed Acyclic Graph(DAG) processing mechanisms
Provide support for REST API calls to monitor processes
Provide native support for Python
Integrate with Microsoft Power BI
You need to select the appropriate data technology to implement the pipeline.
Which data technology should you implement?
- A. HDInsight Spark cluster
- B. Azure Stream Analytics
- C. Azure SQL Data Warehouse
- D. HDInsight Apache Hadoop cluster using MapReduce
- E. HDInsight Apache Storm cluster
Answer: E
Explanation:
Explanation/Reference:
Explanation:
Storm runs topologies instead of the Apache Hadoop MapReduce jobs that you might be familiar with.
Storm topologies are composed of multiple components that are arranged in a directed acyclic graph (DAG). Data flows between the components in the graph. Each component consumes one or more data streams, and can optionally emit one or more streams.
Python can be used to develop Storm components.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/storm/apache-storm-overview
NEW QUESTION 60
You implement an event processing solution using Microsoft Azure Stream Analytics.
The solution must meet the following requirements:
* Ingest data from Blob storage
* Analyze data in real time
* Store processed data in Azure Cosmos DB
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:
1 - Configure Blob storage as input; select items with the TIMESTAMP BY clause
2 - Set up cosmos DB as the output
3 - Create a query statement with the SELECT INTO statement.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs
NEW QUESTION 61
You are a data engineer. You are designing a Hadoop Distributed File System (HDFS) architecture. You plan to use Microsoft Azure Data Lake as a data storage repository.
You must provision the repository with a resilient data schema. You need to ensure the resiliency of the Azure Data Lake Storage. What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: NameNode
An HDFS cluster consists of a single NameNode, a master server that manages the file system namespace and regulates access to files by clients.
Box 2: DataNode
The DataNodes are responsible for serving read and write requests from the file system's clients.
Box 3: DataNode
The DataNodes perform block creation, deletion, and replication upon instruction from the NameNode.
Note: HDFS has a master/slave architecture. An HDFS cluster consists of a single NameNode, a master server that manages the file system namespace and regulates access to files by clients. In addition, there are a number of DataNodes, usually one per node in the cluster, which manage storage attached to the nodes that they run on. HDFS exposes a file system namespace and allows user data to be stored in files. Internally, a file is split into one or more blocks and these blocks are stored in a set of DataNodes. The NameNode executes file system namespace operations like opening, closing, and renaming files and directories. It also determines the mapping of blocks to DataNodes. The DataNodes are responsible for serving read and write requests from the file system's clients. The DataNodes also perform block creation, deletion, and replication upon instruction from the NameNode.
References:
https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html#NameNode+and+DataNodes
NEW QUESTION 62
An application will use Microsoft Azure Cosmos DB as its data solution. The application will use the Cassandra API to support a column-based database type that uses containers to store items.
You need to provision Azure Cosmos DB. Which container name and item name should you use? Each correct answer presents part of the solutions.
NOTE: Each correct answer selection is worth one point.
- A. table
- B. graph
- C. rows
- D. entities
- E. collection
Answer: A,C
Explanation:
B: Depending on the choice of the API, an Azure Cosmos item can represent either a document in a collection, a row in a table or a node/edge in a graph. The following table shows the mapping between API-specific entities to an Azure Cosmos item:
E: An Azure Cosmos container is specialized into API-specific entities as follows:
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/databases-containers-items
NEW QUESTION 63
You are developing a solution to visualize multiple terabytes of geospatial data.
The solution has the following requirements:
*Data must be encrypted.
*Data must be accessible by multiple resources on Microsoft Azure.
You need to provision storage for the solution.
Which four actions should you perform in sequence? To answer, move the appropriate action from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
NEW QUESTION 64
You manage the Microsoft Azure Databricks environment for a company. You must be able to access a private Azure Blob Storage account. Data must be available to all Azure Databricks workspaces. You need to provide the data access.
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 secret scope
Step 2: Add secrets to the scope
Note: dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>") gets the key that has been stored as a secret in a secret scope.
Step 3: Mount the Azure Blob Storage container
You can mount a Blob Storage container or a folder inside a container through Databricks File System - DBFS. The mount is a pointer to a Blob Storage container, so the data is never synced locally.
Note: To mount a Blob Storage container or a folder inside a container, use the following command:
Python
dbutils.fs.mount(
source = "wasbs://<your-container-name>@<your-storage-account-name>.blob.core.windows.net",
mount_point = "/mnt/<mount-name>",
extra_configs = {"<conf-key>":dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>")})
where:
dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>") gets the key that has been stored as a secret in a secret scope.
References:
https://docs.databricks.com/spark/latest/data-sources/azure/azure-storage.html
NEW QUESTION 65
You have an Azure SQL data warehouse.
Using PolyBase, you create table named [Ext].[Items] to query Parquet files stored in Azure Data Lake Storage Gen2 without importing the data to the data warehouse.
The external table has three columns.
You discover that the Parquet files have a fourth column named ItemID.
Which command should you run to add the ItemID column to the external table?
- A. Option B
- B. Option A
- C. Option D
References:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-external-table-transact-sql - D. Option C
Answer: B
NEW QUESTION 66
You deploy an Azure SQL database named DB1 to an Azure SQL server named SQL1.
Currently, only the server admin has access to DB1.
An Azure Active Directory (Azure AD) group named Analysts contains all the users who must have access to DB1.
You have the following data security requirements:
* The Analysts group must have read-only access to all the views and tables in the Sales schema of DB1.
* A manager will decide who can access DB1. The manager will not interact directly with DB1.
* Users must not have to manage a separate password solely to access DB1.
Which four actions should you perform in sequence to meet the data security requirements? 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: From the Azure Portal, set the Active Directory admin for SQL1.
Provision an Azure Active Directory administrator for your Azure SQL Database server.
You can provision an Azure Active Directory administrator for your Azure SQL server in the Azure portal and by using PowerShell.
Step 2: On DB1, create a contained user for the Analysts group by using Transact-SQL Create contained database users in your database mapped to Azure AD identities.
To create an Azure AD-based contained database user (other than the server administrator that owns the database), connect to the database with an Azure AD identity, as a user with at least the ALTER ANY USER permission. Then use the following Transact-SQL syntax:
CREATE USER <Azure_AD_principal_name> FROM EXTERNAL PROVIDER;
Step 3: From Microsoft SQL Server Management Studio (SSMS), sign in to SQL1 by using the account set as the Active Directory admin.
Connect to the user database or data warehouse by using SSMS or SSDT
To confirm the Azure AD administrator is properly set up, connect to the master database using the Azure AD administrator account. To provision an Azure AD-based contained database user (other than the server administrator that owns the database), connect to the database with an Azure AD identity that has access to the database.
Step 4: On DB1, grant the VIEW and SELECT DEFINTION..
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-aad-authentication-configure
NEW QUESTION 67
You are designing a new Lambda architecture on Microsoft Azure.
The real-time processing layer must meet the following requirements:
Ingestion:
* Receive millions of events per second
* Act as a fully managed Platform-as-a-Service (PaaS) solution
* Integrate with Azure Functions
Stream processing:
* Process on a per-job basis
* Provide seamless connectivity with Azure services
* Use a SQL-based query language
Analytical data store:
* Act as a managed service
* Use a document store
* Provide data encryption at rest
You need to identify the correct technologies to build the Lambda architecture using minimal effort. Which technologies should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Azure Event Hubs
This portion of a streaming architecture is often referred to as stream buffering. Options include Azure Event Hubs, Azure IoT Hub, and Kafka.
Incorrect Answers: Not HDInsight Kafka
Azure Functions need a trigger defined in order to run. There is a limited set of supported trigger types, and Kafka is not one of them.
Box 2: Azure Stream Analytics
Azure Stream Analytics provides a managed stream processing service based on perpetually running SQL queries that operate on unbounded streams.
You can also use open source Apache streaming technologies like Storm and Spark Streaming in an HDInsight cluster.
Box 3: Azure SQL Data Warehouse
Azure SQL Data Warehouse provides a managed service for large-scale, cloud-based data warehousing. HDInsight supports Interactive Hive, HBase, and Spark SQL, which can also be used to serve data for analysis.
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/
NEW QUESTION 68
You configure monitoring for an Azure Synapse Analytics implementation. The implementation uses PolyBase to load data from comma-separated value (CSV) files stored in Azure Data Lake Storage Gen 2 using an external table.
Files with an invalid schema cause errors to occur.
You need to monitor for an invalid schema error.
For which error should you monitor?
EXTERNAL TABLE access failed due to internal error: 'Java exception raised on
- A. call to HdfsBridge_Connect: Error [No FileSystem for scheme: wasbs] occurred while accessing external file.' Cannot execute the query "Remote Query" against OLE DB provider "SQLNCLI11"
- B. for linked server "(null)", Query aborted- the maximum reject threshold (0 rows) was reached while reading from an external source: 1 rows rejected out of total 1 rows processed.
EXTERNAL TABLE access failed due to internal error: 'Java exception raised on - C. call to HdfsBridge_Connect: Error [Unable to instantiate LoginClass] occurred while accessing external file.'
- D. call to HdfsBridge_Connect: Error
[com.microsoft.polybase.client.KerberosSecureLogin] occurred while accessing external file.' EXTERNAL TABLE access failed due to internal error: 'Java exception raised on
Answer: B
Explanation:
Customer Scenario:
SQL Server 2016 or SQL DW connected to Azure blob storage. The CREATE EXTERNAL TABLE DDL points to a directory (and not a specific file) and the directory contains files with different schemas.
SSMS Error:
Select query on the external table gives the following error:
Msg 7320, Level 16, State 110, Line 14
Cannot execute the query "Remote Query" against OLE DB provider "SQLNCLI11" for linked server "(null)".
Query aborted-- the maximum reject threshold (0 rows) was reached while reading from an external source: 1 rows rejected out of total 1 rows processed.
Possible Reason:
The reason this error happens is because each file has different schema. The PolyBase external table DDL when pointed to a directory recursively reads all the files in that directory. When a column or data type mismatch happens, this error could be seen in SSMS.
Possible Solution:
If the data for each table consists of one file, then use the filename in the LOCATION section prepended by the directory of the external files. If there are multiple files per table, put each set of files into different directories in Azure Blob Storage and then you can point LOCATION to the directory instead of a particular file. The latter suggestion is the best practices recommended by SQLCAT even if you have one file per table.
Incorrect Answers:
A: Possible Reason: Kerberos is not enabled in Hadoop Cluster.
References:
https://techcommunity.microsoft.com/t5/DataCAT/PolyBase-Setup-Errors-and-Possible-Solutions/ba-p/305297
NEW QUESTION 69
You need to provision the polling data storage account.
How should you configure the storage account? To answer, drag the appropriate Configuration Value to the correct Setting. Each Configuration 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:
NEW QUESTION 70
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