How Many Questions Of DP-201 Exam Prep

NEW QUESTION 1

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.
You are designing an Azure SQL Database that will use elastic pools. You plan to store data about customers in a table. Each record uses a value for CustomerID.
You need to recommend a strategy to partition data based on values in CustomerID. Proposed Solution: Separate data into customer regions by using vertical partitioning. Does the solution meet the goal?

• A. Yes
• B. No

Answer: B

Explanation:
Vertical partitioning is used for cross-database queries. Instead we should use Horizontal Partitioning, which also is called charding.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-query-overview

NEW QUESTION 2

You are designing a data processing solution that will implement the lambda architecture pattern. The solution will use Spark running on HDInsight for data processing.
You need to recommend a data storage technology for the solution.
Which two technologies should you recommend? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

• A. Azure Cosmos DB
• B. Azure Service Bus
• C. Azure Storage Queue
• D. Apache Cassandra
• E. Kafka HDInsight

Answer: AE

Explanation:
To implement a lambda architecture on Azure, you can combine the following technologies to accelerate realtime big data analytics:
Azure Cosmos DB, the industry's first globally distributed, multi-model database service.
Apache Spark for Azure HDInsight, a processing framework that runs large-scale data analytics applications
Azure Cosmos DB change feed, which streams new data to the batch layer for HDInsight to process The Spark to Azure Cosmos DB Connector
E: You can use Apache Spark to stream data into or out of Apache Kafka on HDInsight using DStreams. References:
https://docs.microsoft.com/en-us/azure/cosmos-db/lambda-architecture

NEW QUESTION 3

You need to recommend the appropriate storage and processing solution? What should you recommend?

• A. Enable auto-shrink on the database.
• B. Flush the blob cache using Windows PowerShell.
• C. Enable Apache Spark RDD (RDD) caching.
• D. Enable Databricks IO (DBIO) caching.
• E. Configure the reading speed using Azure Data Studio.

Answer: C

Explanation:
Scenario: You must be able to use a file system view of data stored in a blob. You must build an architecture that will allow Contoso to use the DB FS filesystem layer over a blob store.
Databricks File System (DBFS) is a distributed file system installed on Azure Databricks clusters. Files in DBFS persist to Azure Blob storage, so you won’t lose data even after you terminate a cluster.
The Databricks Delta cache, previously named Databricks IO (DBIO) caching, accelerates data reads by creating copies of remote files in nodes’ local storage using a fast intermediate data format. The data is cached automatically whenever a file has to be fetched from a remote location. Successive reads of the same data are then performed locally, which results in significantly improved reading speed.

NEW QUESTION 4

You have an on-premises MySQL database that is 800 GB in size.
You need to migrate a MySQL database to Azure Database for MySQL. You must minimize service interruption to live sites or applications that use the database.
What should you recommend?

• A. Azure Database Migration Service
• B. Dump and restore
• C. Import and export
• D. MySQL Workbench

Answer: A

Explanation:
You can perform MySQL migrations to Azure Database for MySQL with minimal downtime by using the newly introduced continuous sync capability for the Azure Database Migration Service (DMS). This functionality limits the amount of downtime that is incurred by the application. References:
https://docs.microsoft.com/en-us/azure/mysql/howto-migrate-online

NEW QUESTION 5

A company is designing a solution that uses Azure Databricks.
The solution must be resilient to regional Azure datacenter outages. You need to recommend the redundancy type for the solution. What should you recommend?

• A. Read-access geo-redundant storage
• B. Locally-redundant storage
• C. Geo-redundant storage
• D. Zone-redundant storage

Answer: C

Explanation:
If your storage account has GRS enabled, then your data is durable even in the case of a complete regional outage or a disaster in which the primary region isn’t recoverable.
References:
https://medium.com/microsoftazure/data-durability-fault-tolerance-resilience-in-azure-databricks- 95392982bac7

NEW QUESTION 6

You need to design the vehicle images storage solution. What should you recommend?

• A. Azure Media Services
• B. Azure Premium Storage account
• C. Azure Redis Cache
• D. Azure Cosmos DB

Answer: B

Explanation:
Premium Storage stores data on the latest technology Solid State Drives (SSDs) whereas Standard Storage stores data on Hard Disk Drives (HDDs). Premium Storage is designed for Azure Virtual Machine workloads which require consistent high IO performance and low latency in order to host IO intensive workloads like OLTP, Big Data, and Data Warehousing on platforms like SQL Server, MongoDB, Cassandra, and others. With Premium Storage, more customers will be able to lift-and-shift demanding enterprise applications to the cloud.
Scenario: Traffic sensors will occasionally capture an image of a vehicle for debugging purposes. You must optimize performance of saving/storing vehicle images.
The impact of vehicle images on sensor data throughout must be minimized. References:
https://azure.microsoft.com/es-es/blog/introducing-premium-storage-high-performance-storage-for-azure-virtual

NEW QUESTION 7

A company stores data in multiple types of cloud-based databases.
You need to design a solution to consolidate data into a single relational database. Ingestion of data will occur at set times each day.
What should you recommend?

• A. SQL Server Migration Assistant
• B. SQL Data Sync
• C. Azure Data Factory
• D. Azure Database Migration Service
• E. Data Migration Assistant

Answer: C

Explanation:
https://docs.microsoft.com/en-us/azure/data-factory/introduction
https://azure.microsoft.com/en-us/blog/operationalize-azure-databricks-notebooks-using-data-factory/ https://azure.microsoft.com/en-us/blog/data-ingestion-into-azure-at-scale-made-easier-with-latest-enhancements

NEW QUESTION 8

You need to design the solution for analyzing customer data. What should you recommend?

• A. Azure Databricks
• B. Azure Data Lake Storage
• C. Azure SQL Data Warehouse
• D. Azure Cognitive Services
• E. Azure Batch

Answer: A

Explanation:
Customer data must be analyzed using managed Spark clusters. You create spark clusters through Azure Databricks. References:
https://docs.microsoft.com/en-us/azure/azure-databricks/quickstart-create-databricks-workspace-portal

NEW QUESTION 9

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 is developing a solution to manage inventory data for a group of automotive repair shops. The solution will use Azure SQL Data Warehouse as the data store.
Shops will upload data every 10 days.
Data corruption checks must run each time data is uploaded. If corruption is detected, the corrupted data must be removed.
You need to ensure that upload processes and data corruption checks do not impact reporting and analytics processes that use the data warehouse.
Proposed solution: Create a user-defined restore point before data is uploaded. Delete the restore point after data corruption checks complete.
Does the solution meet the goal?

• A. Yes
• B. No

Answer: A

Explanation:
User-Defined Restore Points
This feature enables you to manually trigger snapshots to create restore points of your data warehouse before and after large modifications. This capability ensures that restore points are logically consistent, which provides additional data protection in case of any workload interruptions or user errors for quick recovery time.
Note: A data warehouse restore is a new data warehouse that is created from a restore point of an existing or deleted data warehouse. Restoring your data warehouse is an essential part of any business continuity and disaster recovery strategy because it re-creates your data after accidental corruption or deletion.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore

NEW QUESTION 10

A company purchases loT devices to monitor manufacturing machinery. The company uses an loT appliance to communicate with the loT devices.
The company must be able to monitor the devices in real-time. You need to design the solution.
What should you recommend?

• A. Azure Stream Analytics cloud job using Azure PowerShell
• B. Azure Analysis Services using Azure Portal
• C. Azure Data Factory instance using Azure Portal
• D. Azure Analysis Services using Azure PowerShell

Answer: D

NEW QUESTION 11

You need to design the system for notifying law enforcement officers about speeding vehicles.
How should you design the pipeline? To answer, drag the appropriate services to the correct locations. Each service 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.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:

NEW QUESTION 12

You plan to use Azure SQL Database to support a line of business app.
You need to identify sensitive data that is stored in the database and monitor access to the data. Which three actions should you recommend? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

• A. Enable Data Discovery and Classification.
• B. Implement Transparent Data Encryption (TDE).
• C. Enable Auditing.
• D. Run Vulnerability Assessment.
• E. Use Advanced Threat Protection.

Answer: CDE

NEW QUESTION 13

A company is evaluating data storage solutions.
You need to recommend a data storage solution that meets the following requirements: Minimize costs for storing blob objects.
Optimize access for data that is infrequently accessed. Data must be stored for at least 30 days.
Data availability must be at least 99 percent. What should you recommend?

• A. Premium
• B. Cold
• C. Hot
• D. Archive

Answer: B

Explanation:
Azure’s cool storage tier, also known as Azure cool Blob storage, is for infrequently-accessed data that needs to be stored for a minimum of 30 days. Typical use cases include backing up data before tiering to archival systems, legal data, media files, system audit information, datasets used for big data analysis and more.
The storage cost for this Azure cold storage tier is lower than that of hot storage tier. Since it is expected that the data stored in this tier will be accessed less frequently, the data access charges are high when compared to hot tier. There are no additional changes required in your applications as these tiers can be accessed using
APIs in the same manner that you access Azure storage. References:
https://cloud.netapp.com/blog/low-cost-storage-options-on-azure

NEW QUESTION 14

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.
You are designing an Azure SQL Database that will use elastic pools. You plan to store data about customers in a table. Each record uses a value for CustomerID.
You need to recommend a strategy to partition data based on values in CustomerID. Proposed Solution: Separate data into shards by using horizontal partitioning.
Does the solution meet the goal?

• A. Yes
• B. No

Answer: A

Explanation:
Horizontal Partitioning - Sharding: Data is partitioned horizontally to distribute rows across a scaled out data
tier. With this approach, the schema is identical on all participating databases. This approach is also called “sharding”. Sharding can be performed and managed using (1) the elastic database tools libraries or (2) selfsharding.
An elastic query is used to query or compile reports across many shards. References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-query-overview

NEW QUESTION 15

You are designing a solution for a company. You plan to use Azure Databricks. You need to recommend workloads and tiers to meet the following requirements:
Provide managed clusters for running production jobs.
Provide persistent clusters that support auto-scaling for analytics processes.
Provide role-based access control (RBAC) support for Notebooks.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:
Box 1: Data Engineering Only
Box 2: Data Engineering and Data Analytics Box 3: Standard
Box 4: Data Analytics only Box 5: Premium
Premium required for RBAC. Data Analytics Premium Tier provide interactive workloads to analyze data collaboratively with notebooks
References:
https://azure.microsoft.com/en-us/pricing/details/databricks/

NEW QUESTION 16

You are designing a solution for a company. The solution will use model training for objective classification. You need to design the solution.
What should you recommend?

• A. an Azure Cognitive Services application
• B. a Spark Streaming job
• C. interactive Spark queries
• D. Power BI models
• E. a Spark application that uses Spark MLib.

Answer: E

Explanation:
Spark in SQL Server big data cluster enables AI and machine learning.
You can use Apache Spark MLlib to create a machine learning application to do simple predictive analysis on an open dataset.
MLlib is a core Spark library that provides many utilities useful for machine learning tasks, including utilities that are suitable for:
Classification
Regression
Clustering
Topic modeling
Singular value decomposition (SVD) and principal component analysis (PCA)
Hypothesis testing and calculating sample statistics
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-machine-learning-mllib-ipython

NEW QUESTION 17

You need to recommend a backup strategy for CONT_SQL1 and CONT_SQL2. What should you recommend?

• A. Use AzCopy and store the data in Azure.
• B. Configure Azure SQL Database long-term retention for all databases.
• C. Configure Accelerated Database Recovery.
• D. Use DWLoader.

Answer: B

Explanation:
Scenario: The database backups have regulatory purposes and must be retained for seven years.

NEW QUESTION 18

You are evaluating data storage solutions to support a new application.
You need to recommend a data storage solution that represents data by using nodes and relationships in graph structures.
Which data storage solution should you recommend?

• A. Blob Storage
• B. Cosmos DB
• C. Data Lake Store
• D. HDInsight

Answer: B

Explanation:
For large graphs with lots of entities and relationships, you can perform very complex analyses very quickly. Many graph databases provide a query language that you can use to traverse a network of relationships efficiently.
Relevant Azure service: Cosmos DB
References:
https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview

NEW QUESTION 19

You design data engineering solutions for a company.
You must integrate on-premises SQL Server data into an Azure solution that performs Extract-Transform-Load (ETL) operations have the following requirements:
Develop a pipeline that can integrate data and run notebooks.
Develop notebooks to transform the data.
Load the data into a massively parallel processing database for later analysis. You need to recommend a solution.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:

NEW QUESTION 20

You need to design the SensorData collection.
What should you recommend? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:
Box 1: Eventual
Traffic data insertion rate must be maximized.
Sensor data must be stored in a Cosmos DB named treydata in a collection named SensorData
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.
Box 2: License plate
This solution reports on all data related to a specific vehicle license plate. The report must use data from the SensorData collection.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels

NEW QUESTION 21

You are developing a solution that performs real-time analysis of IoT data in the cloud. The solution must remain available during Azure service updates.
You need to recommend a solution.
Which two actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A. Deploy an Azure Stream Analytics job to two separate regions that are not in a pair.
• B. Deploy an Azure Stream Analytics job to each region in a paired region.
• C. Monitor jobs in both regions for failure.
• D. Monitor jobs in the primary region for failure.
• E. Deploy an Azure Stream Analytics job to one region in a paired region.

Answer: BC

Explanation:
Stream Analytics guarantees jobs in paired regions are updated in separate batches. As a result there is a sufficient time gap between the updates to identify potential breaking bugs and remediate them.
Customers are advised to deploy identical jobs to both paired regions.
In addition to Stream Analytics internal monitoring capabilities, customers are also advised to monitor the jobs as if both are production jobs. If a break is identified to be a result of the Stream Analytics service update, escalate appropriately and fail over any downstream consumers to the healthy job output. Escalation to support will prevent the paired region from being affected by the new deployment and maintain the integrity of the paired jobs.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-reliability

NEW QUESTION 22

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.
You are designing an HDInsight/Hadoop cluster solution that uses Azure Data Lake Gen1 Storage. The solution requires POSIX permissions and enables diagnostics logging for auditing.
You need to recommend solutions that optimize storage.
Proposed Solution: Implement compaction jobs to combine small files into larger files. Does the solution meet the goal?

• A. Yes
• B. No

Answer: A

Explanation:
Depending on what services and workloads are using the data, a good size to consider for files is 256 MB or greater. If the file sizes cannot be batched when landing in Data Lake Storage Gen1, you can have a separate compaction job that combines these files into larger ones.
Note: POSIX permissions and auditing in Data Lake Storage Gen1 comes with an overhead that becomes apparent when working with numerous small files. As a best practice, you must batch your data into larger files versus writing thousands or millions of small files to Data Lake Storage Gen1. Avoiding small file sizes can have multiple benefits, such as:
Lowering the authentication checks across multiple files Reduced open file connections
Faster copying/replication
Fewer files to process when updating Data Lake Storage Gen1 POSIX permissions References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-best-practices

NEW QUESTION 23

You need to design the encryption strategy for the tagging data and customer data.
What should you recommend? To answer, drag the appropriate setting to the correct drop targets. Each source 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.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:
All cloud data must be encrypted at rest and in transit. Box 1: Transparent data encryption
Encryption of the database file is performed at the page level. The pages in an encrypted database are encrypted before they are written to disk and decrypted when read into memory.
Box 2: Encryption at rest
Encryption at Rest is the encoding (encryption) of data when it is persisted. References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption?view= https://docs.microsoft.com/en-us/azure/security/azure-security-encryption-atrest

NEW QUESTION 24

You plan to deploy an Azure SQL Database instance to support an application. You plan to use the DTUbased purchasing model.
Backups of the database must be available for 30 days and point-in-time restoration must be possible. You need to recommend a backup and recovery policy.
What are two possible ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

• A. Use the Premium tier and the default backup retention policy.
• B. Use the Basic tier and the default backup retention policy.
• C. Use the Standard tier and the default backup retention policy.
• D. Use the Standard tier and configure a long-term backup retention policy.
• E. Use the Premium tier and configure a long-term backup retention policy.

Answer: DE

Explanation:
The default retention period for a database created using the DTU-based purchasing model depends on the service tier:
Basic service tier is 1 week.
Standard service tier is 5 weeks.
Premium service tier is 5 weeks.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-long-term-retention

NEW QUESTION 25

You design data engineering solutions for a company.
A project requires analytics and visualization of large set of data. The project has the following requirements:
Notebook scheduling
Cluster automation
Power BI Visualization
You need to recommend the appropriate Azure service. Which Azure service should you recommend?

• A. Azure Batch
• B. Azure Stream Analytics
• C. Azure ML Studio
• D. Azure Databricks
• E. Azure HDInsight

Answer: D

Explanation:
A databrick job is a way of running a notebook or JAR either immediately or on a scheduled basis.
Azure Databricks has two types of clusters: interactive and job. Interactive clusters are used to analyze data collaboratively with interactive notebooks. Job clusters are used to run fast and robust automated workloads using the UI or API.
You can visualize Data with Azure Databricks and Power BI Desktop.
References:
https://docs.azuredatabricks.net/user-guide/clusters/index.html https://docs.azuredatabricks.net/user-guide/jobs.html

NEW QUESTION 26
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