[Dec 09, 2021] DP-200 Exam Brain Dumps - Study Notes and Theory
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Microsoft DP-200 Exam Syllabus Topics:
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NEW QUESTION 143
You need to ensure that Azure Data Factory pipelines can be deployed. How should you configure authentication and authorization for deployments? To answer, select the appropriate options in the answer choices.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
References:
https://docs.microsoft.com/en-us/azure/role-based-access-control/overview
NEW QUESTION 144
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 Storage account that contains 100 GB of files. The files contain text and numerical values.
75% of the rows contain description data that has an average length of 1.1 MB.
You plan to copy the data from the storage account to an Azure SQL data warehouse.
You need to prepare the files to ensure that the data copies quickly.
Solution: You copy the files to a table that has a columnstore index.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation
Instead modify the files to ensure that each row is less than 1 MB.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data
NEW QUESTION 145
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 section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
A company uses Azure Data Lake Gen 1 Storage to store big data related to consumer behavior.
You need to implement logging.
Solution: Use information stored in Azure Active Directory reports.
Does the solution meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Instead configure Azure Data Lake Storage diagnostics to store logs and metrics in a storage account.
Note:
You can enable diagnostic logging for your Azure Data Lake Storage Gen1 accounts, blobs, files, queues and tables.
Diagnostic logs aren't available for Data Lake Storage Gen2 accounts [as of August 2019].
References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-diagnostic-logs
https://github.com/MicrosoftDocs/azure-docs/issues/34286
NEW QUESTION 146
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 Standard cluster for the jobs.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation
We would need a High Concurrency cluster for 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 147 
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 increase the size of db2 to store up to 250 GB of data.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
1. In Azure Portal, navigate to the SQL databases page, select the db2 database , and choose Configure performance
2. Click on Standard and Adjust the Storage size to 250 GB
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-single-databases-manage
NEW QUESTION 148
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:
Explanation:
Box 1: transparent data encryption
TDE with customer-managed keys in Azure Key Vault allows to encrypt the Database Encryption Key (DEK) with a customer-managed asymmetric key called TDE Protector. This is also generally referred to as Bring Your Own Key (BYOK) support for Transparent Data Encryption.
Note: Transparent data encryption encrypts the storage of an entire database by using a symmetric key called the database encryption key. This database encryption key is protected by the transparent data encryption protector.
Transparent data encryption (TDE) helps protect Azure SQL Database, Azure SQL Managed Instance, and Azure Data Warehouse against the threat of malicious offline activity by encrypting data at rest. It performs real-time encryption and decryption of the database, associated backups, and transaction log files at rest without requiring changes to the application.
Box 2: Storage account keys
You can rely on Microsoft-managed keys for the encryption of your storage account, or you can manage encryption with your own keys, together with Azure Key Vault.
References:
https://docs.microsoft.com/en-us/azure/sql-database/transparent-data-encryption-azure-sql
https://docs.microsoft.com/en-us/azure/storage/common/storage-service-encryption
NEW QUESTION 149
You implement an Azure SQL Data Warehouse instance.
You plan to migrate the largest fact table to Azure SQL Data Warehouse. The table resides on Microsoft SQL Server on-premises and is 10 terabytes (TB) is size.
Incoming queries use the primary key Sale Key column to retrieve data as displayed in the following table:
You need to distribute the large fact table across multiple nodes to optimize performance of the table.
Which technology should you use?
- A. hash distributed table with clustered index
- B. heap table with distribution replicate
- C. round robin distributed table with clustered ColumnStore index
- D. hash distributed table with clustered ColumnStore index
- E. round robin distributed table with clustered index
Answer: D
Explanation:
Explanation
Hash-distributed tables improve query performance on large fact tables.
Columnstore indexes can achieve up to 100x better performance on analytics and data warehousing workloads and up to 10x better data compression than traditional rowstore indexes.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
https://docs.microsoft.com/en-us/sql/relational-databases/indexes/columnstore-indexes-query-performance
NEW QUESTION 150
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 ensure that you can recover any blob data from an Azure Storage account named storage10543936 up to 10 days after the data is deleted.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
Enable soft delete for blobs on your storage account by using Azure portal:
1. In the Azure portal, select your storage account.
2. Navigate to the Data Protection option under Blob Service.
3. Click Enabled under Blob soft delete
4. Enter the number of days you want to retain for under Retention policies. Here enter 10.
5. Choose the Save button to confirm your Data Protection settings
Note: Azure Storage now offers soft delete for blob objects so that you can more easily recover your data when it is erroneously modified or deleted by an application or other storage account user. Currently you can retain soft deleted data for between 1 and 365 days.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-soft-delete
NEW QUESTION 151
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 a container named Sales in an Azure Cosmos DB database. Sales has 120 GB of data. Each entry in Sales has the following structure.
The partition key is set to the OrderId attribute.
Users report that when they perform queries that retrieve data by ProductName, the queries take longer than expected to complete.
You need to reduce the amount of time it takes to execute the problematic queries.
Solution: You create a lookup collection that uses ProductName as a partition key.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
One option is to have a lookup collection "ProductName" for the mapping of "ProductName" to "OrderId".
References:
https://azure.microsoft.com/sv-se/blog/azure-cosmos-db-partitioning-design-patterns-part-1/
NEW QUESTION 152
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 replicate db1 to a new Azure SQL server named db1-copy10543936 in the US West region.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
1. In the Azure portal, browse to the database db1-copy10543936 that you want to set up for geo-replication.
2. On the SQL database page, select geo-replication, and then select the region to create the secondary database: US West region
3. Select or configure the server and pricing tier for the secondary database.
4. Click Create to add the secondary.
5. The secondary database is created and the seeding process begins.
6. When the seeding process is complete, the secondary database displays its status.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-active-geo-replication-portal
NEW QUESTION 153
Which masking functions should you implement for each column to meet the data masking requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview Overview ADatum Corporation is a retailer that sells products through two sales channels: retail stores and a website.
NEW QUESTION 154
You are responsible for providing access to an Azure Data Lake Storage Gen2 account.
Your user account has contributor access to the storage account, and you have the application ID access key.
You plan to use PolyBase to load data into Azure SQL data warehouse.
You need to configure PolyBase to connect the data warehouse to the storage account.
Which three components should you create in sequence? To answer, move the appropriate components from the list of components to the answer are and arrange them in the correct order.
Answer:
Explanation:
Explanation
Step 1: a database scoped credential
To access your Data Lake Storage account, you will need to create a Database Master Key to encrypt your credential secret used in the next step. You then create a database scoped credential.
Step 2: an external data source
Create the external data source. Use the CREATE EXTERNAL DATA SOURCE command to store the location of the data. Provide the credential created in the previous step.
Step 3: an external file format
Configure data format: To import the data from Data Lake Storage, you need to specify the External File Format. This object defines how the files are written in Data Lake Storage.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure-data-lake-store
NEW QUESTION 155
A company plans to use Platform-as-a-Service (PaaS) to create the new data pipeline process. The process must meet the following requirements.
Ingest:
*Access multiple data sources
*Provide the ability to orchestrate workflow
*Provide the capability to run SQL Server Integration Services packages.
Store:
*Optimize storage for big data workloads.
*Provide encryption of data at rest.
*Operate with no size limits.
Prepare and Train:
*Provide a fully-managed and interactive workspace for exploration and visualization.
*Provide the ability to program in R, SQL, Python, Scala, and Java.
*Provide seamless user authentication with Azure Active Directory.
Model & Serve:
*Implement native columnar storage.
*Support for the SQL language
*Provide support for structured streaming.
You need to build the data integration pipeline.
Which technologies should you use? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Explanation
Ingest: Azure Data Factory
Azure Data Factory pipelines can execute SSIS packages.
In Azure, the following services and tools will meet the core requirements for pipeline orchestration, control flow, and data movement: Azure Data Factory, Oozie on HDInsight, and SQL Server Integration Services (SSIS).
Store: Data Lake Storage
Data Lake Storage Gen1 provides unlimited storage.
Note: Data at rest includes information that resides in persistent storage on physical media, in any digital format. Microsoft Azure offers a variety of data storage solutions to meet different needs, including file, disk, blob, and table storage. Microsoft also provides encryption to protect Azure SQL Database, Azure Cosmos DB, and Azure Data Lake.
Prepare and Train: Azure Databricks
Azure Databricks provides enterprise-grade Azure security, including Azure Active Directory integration.
With Azure Databricks, you can set up your Apache Spark environment in minutes, autoscale and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch and scikit-learn.
Model and Serve: SQL Data Warehouse
SQL Data Warehouse stores data into relational tables with columnar storage.
Azure SQL Data Warehouse connector now offers efficient and scalable structured streaming write support for SQL Data Warehouse. Access SQL Data Warehouse from Azure Databricks using the SQL Data Warehouse connector.
References:
https://docs.microsoft.com/bs-latn-ba/azure/architecture/data-guide/technology-choices/pipeline-orchestration-d
https://docs.microsoft.com/en-us/azure/azure-databricks/what-is-azure-databricks
NEW QUESTION 156
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:
Explanation
Box 1: New-AzStorageContainer
# Example: Create a blob container. This holds the default data store for the cluster.
New-AzStorageContainer `
-Name $clusterName `
-Context $defaultStorageContext
$sparkConfig = New-Object "System.Collections.Generic.Dictionary``2[System.String,System.String]"
$sparkConfig.Add("spark", "2.3")
Box 2: Spark
Spark provides primitives for in-memory cluster computing. A Spark job can load and cache data into memory and query it repeatedly. In-memory computing is much faster than disk-based applications than disk-based applications, such as Hadoop, which shares data through Hadoop distributed file system (HDFS).
Box 3: New-AzureRMHDInsightCluster
# Create the HDInsight cluster. Example:
New-AzHDInsightCluster `
-ResourceGroupName $resourceGroupName `
-ClusterName $clusterName `
-Location $location `
-ClusterSizeInNodes $clusterSizeInNodes `
-ClusterType $"Spark" `
-OSType "Linux" `
Box 4: Spark
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.
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 157
You are responsible for providing access to an Azure Data Lake Storage Gen2 account.
Your user account has contributor access to the storage account, and you have the application ID access key.
You plan to use PolyBase to load data into Azure SQL data warehouse.
You need to configure PolyBase to connect the data warehouse to the storage account.
Which three components should you create in sequence? To answer, move the appropriate components from the list of components to the answer are and arrange them in the correct order.
Answer:
Explanation:
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure-data-lake-store
NEW QUESTION 158 
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 classify the following information as Confidential:
* Database: db3
* Schema: SalesLT
* Table: Customer
* Column: Phone Information
* Type: Contact Info
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
1. In Azure Portal, locate and select database db3.
2. Select Security and Advance Data Security, and Click Enable advanced Data Security Protection
3. Click the Data Discovery & Classification card.
4. Click on Add classification in the top menu of the window.
5. In the context window that opens, select the schema > table > column that you want to classify, and the information type and sensitivity label. Then click on the blue Add classification button at the bottom of the context window.
Select/enter the following
* Schema: SalesLT
* Table: Customer
* Column: Phone Information
* Information type: Contact Info
6. To complete your classification and persistently label (tag) the database columns with the new classification metadata, click on Save in the top menu of the window.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-data-discovery-and-classification
NEW QUESTION 159
A company builds an application to allow developers to share and compare code. The conversations, code snippets, and links shared by people in the application are stored in a Microsoft Azure SQL Database instance.
The application allows for searches of historical conversations and code snippets.
When users share code snippets, the code snippet is compared against previously share code snippets by using a combination of Transact-SQL functions including SUBSTRING, FIRST_VALUE, and SQRT. If a match is found, a link to the match is added to the conversation.
Customers report the following issues:
* Delays occur during live conversations
* A delay occurs before matching links appear after code snippets are added to conversations You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology 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: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view
NEW QUESTION 160
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:
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-pool
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-service-tier-hyperscale-faq
NEW QUESTION 161
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