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Free demo questions for Microsoft DP-201 Exam Dumps Below:
NEW QUESTION 1
You are designing an Azure Data Factory pipeline for processing data. The pipeline will process data that is stored in general-purpose standard Azure storage.
You need to ensure that the compute environment is created on-demand and removed when the process is completed.
Which type of activity should you recommend?
- A. Databricks Python activity
- B. Data Lake Analytics U-SQL activity
- C. HDInsight Pig activity
- D. Databricks Jar activity
Answer: C
Explanation:
The HDInsight Pig activity in a Data Factory pipeline executes Pig queries on your own or on-demand HDInsight cluster.
References:
https://docs.microsoft.com/en-us/azure/data-factory/transform-data-using-hadoop-pig
NEW QUESTION 2
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 3
You need to design the runtime environment for the Real Time Response system. What should you recommend?
- A. General Purpose nodes without the Enterprise Security package
- B. Memory Optimized Nodes without the Enterprise Security package
- C. Memory Optimized nodes with the Enterprise Security package
- D. General Purpose nodes with the Enterprise Security package
Answer: B
NEW QUESTION 4
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 5
You need to ensure that performance requirements for Backtrack reports are met.
What should you recommend? To answer, drag the appropriate technologies to the correct locations. 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.
- A. Mastered
- B. Not Mastered
Answer: A
Explanation:
Box 1: Cosmos DB indexes
The report for Backtrack must execute as quickly as possible.
You can override the default indexing policy on an Azure Cosmos container, this could be useful if you want to tune the indexing precision to improve the query performance or to reduce the consumed storage.
Box 2: Cosmos DB TTL
This solution reports on all data related to a specific vehicle license plate. The report must use data from the SensorData collection. Users must be able to filter vehicle data in the following ways:
vehicles on a specific road
vehicles driving above the speed limit
Note: With Time to Live or TTL, Azure Cosmos DB provides the ability to delete items automatically from a container after a certain time period. By default, you can set time to live at the container level and override the value on a per-item basis. After you set the TTL at a container or at an item level, Azure Cosmos DB will automatically remove these items after the time period, since the time they were last modified.
NEW QUESTION 6
You are designing an Azure SQL Data Warehouse. You plan to load millions of rows of data into the data warehouse each day.
You must ensure that staging tables are optimized for data loading. You need to design the staging tables.
What type of tables should you recommend?
- A. Round-robin distributed table
- B. Hash-distributed table
- C. Replicated table
- D. External table
Answer: A
Explanation:
To achieve the fastest loading speed for moving data into a data warehouse table, load data into a staging table. Define the staging table as a heap and use round-robin for the distribution option.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data
NEW QUESTION 7
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 8
You have a Windows-based solution that analyzes scientific data. You are designing a cloud-based solution that performs real-time analysis of the data.
You need to design the logical flow for the solution.
Which two actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Send data from the application to an Azure Stream Analytics job.
- B. Use an Azure Stream Analytics job on an edge devic
- C. Ingress data from an Azure Data Factory instance and build queries that output to Power BI.
- D. Use an Azure Stream Analytics job in the clou
- E. Ingress data from the Azure Event Hub instance and build queries that output to Power BI.
- F. Use an Azure Stream Analytics job in the clou
- G. Ingress data from an Azure Event Hub instance and build queries that output to Azure Data Lake Storage.
- H. Send data from the application to Azure Data Lake Storage.
- I. Send data from the application to an Azure Event Hub instance.
Answer: CF
Explanation:
Stream Analytics has first-class integration with Azure data streams as inputs from three kinds of resources: Azure Event Hubs
Azure IoT Hub Azure Blob storage References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs
NEW QUESTION 9
A company has an application that uses Azure SQL Database as the data store.
The application experiences a large increase in activity during the last month of each year.
You need to manually scale the Azure SQL Database instance to account for the increase in data write operations.
Which scaling method should you recommend?
- A. Scale up by using elastic pools to distribute resources.
- B. Scale out by sharding the data across databases.
- C. Scale up by increasing the database throughput units.
Answer: C
Explanation:
As of now, the cost of running an Azure SQL database instance is based on the number of Database Throughput Units (DTUs) allocated for the database. When determining the number of units to allocate for the
solution, a major contributing factor is to identify what processing power is needed to handle the volume of expected requests.
Running the statement to upgrade/downgrade your database takes a matter of seconds.
NEW QUESTION 10
You are designing an Azure SQL Data Warehouse for a financial services company. Azure Active Directory will be used to authenticate the users.
You need to ensure that the following security requirements are met:
Department managers must be able to create new database.
The IT department must assign users to databases.
Permissions granted must be minimized.
Which role memberships should you recommend? To answer, drag the appropriate roles to the correct groups. Each role 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.
- A. Mastered
- B. Not Mastered
Answer: A
Explanation:
Box 1: dbmanager
Members of the dbmanager role can create new databases. Box 2: db_accessadmin
Members of the db_accessadmin fixed database role can add or remove access to the database for Windows logins, Windows groups, and SQL Server logins.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-manage-logins
NEW QUESTION 11
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 12
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 13
You need to design a backup solution for the processed customer data. What should you include in the design?
- A. AzCopy
- B. AdlCopy
- C. Geo-Redundancy
- D. Geo-Replication
Answer: C
Explanation:
Scenario: All data must be backed up in case disaster recovery is required.
Geo-redundant storage (GRS) is designed to provide at least 99.99999999999999% (16 9's) durability of objects over a given year by replicating your data to a secondary region that is hundreds of miles away from
the primary region. 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://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy-grs
NEW QUESTION 14
A company has locations in North America and Europe. The company uses Azure SQL Database to support business apps.
Employees must be able to access the app data in case of a region-wide outage. A multi-region availability solution is needed with the following requirements:
Read-access to data in a secondary region must be available only in case of an outage of the primary region.
The Azure SQL Database compute and storage layers must be integrated and replicated together.
You need to design the multi-region high availability solution.
What should you recommend? To answer, select the appropriate values in the answer area.
NOTE: Each correct selection is worth one point.
- A. Mastered
- B. Not Mastered
Answer: A
Explanation:
Box 1: Standard
The following table describes the types of storage accounts and their capabilities:
Box 2: Geo-redundant storage
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.
Note: If you opt for GRS, you have two related options to choose from:
GRS replicates your data to another data center in a secondary region, but that data is available to be read only if Microsoft initiates a failover from the primary to secondary region.
Read-access geo-redundant storage (RA-GRS) is based on GRS. RA-GRS replicates your data to another data center in a secondary region, and also provides you with the option to read from the secondary region. With RA-GRS, you can read from the secondary region regardless of whether Microsoft initiates a failover from the primary to secondary region.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-introduction https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy-grs
NEW QUESTION 15
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 16
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 17
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: Ensure that files stored are smaller than 250MB. Does the solution meet the goal?
- A. Yes
- B. No
Answer: B
Explanation:
Ensure that files stored are larger, not smaller than 250MB.
You can have a separate compaction job that combines these files into larger ones.
Note: The file 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 18
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: Ensure that files stored are larger than 250MB. 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 19
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 20
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 21
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 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.
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: Insert data from shops and perform the data corruption check in a transaction. Rollback transfer if corruption is detected.
Does the solution meet the goal?
- A. Yes
- B. No
Answer: B
Explanation:
Instead, create a user-defined restore point before data is uploaded. Delete the restore point after data corruption checks complete.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore
NEW QUESTION 23
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