[Oct-2021] Pass Microsoft DP-201 Exam in First Attempt Guaranteed!
Full DP-201 Practice Test and 207 unique questions with explanations waiting just for you, get it now!
NEW QUESTION 17
What should you recommend using to secure sensitive customer contact information?
- A. data labels
- B. column-level security
- C. Transparent Data Encryption (TDE)
- D. row-level security
Answer: B
Explanation:
Scenario: Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
Always Encrypted is a feature designed to protect sensitive data stored in specific database columns from access (for example, credit card numbers, national identification numbers, or data on a need to know basis).
This includes database administrators or other privileged users who are authorized to access the database to perform management tasks, but have no business need to access the particular data in the encrypted columns. The data is always encrypted, which means the encrypted data is decrypted only for processing by client applications with access to the encryption key.
Incorrect Answers:
A: Transparent Data Encryption (TDE) encrypts SQL Server, Azure SQL Database, and Azure SQL Data Warehouse data files, known as encrypting data at rest. TDE does not provide encryption across communication channels.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-security-overview Design for data security and compliance Testlet 4 Case study This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Background
Current environment
The company has the following virtual machines (VMs):
Requirements
Storage and processing
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. The architecture will need to support data files, libraries, and images. Additionally, it must provide a web-based interface to documents that contain runnable command, visualizations, and narrative text such as a notebook.
CONT_SQL3 requires an initial scale of 35000 IOPS.
CONT_SQL1 and CONT_SQL2 must use the vCore model and should include replicas. The solution must support 8000 IOPS.
The storage should be configured to optimized storage for database OLTP workloads.
Migration
* You must be able to independently scale compute and storage resources.
* You must migrate all SQL Server workloads to Azure. You must identify related machines in the on- premises environment, get disk size data usage information.
* Data from SQL Server must include zone redundant storage.
* You need to ensure that app components can reside on-premises while interacting with components that run in the Azure public cloud.
* SAP data must remain on-premises.
* The Azure Site Recovery (ASR) results should contain per-machine data.
Business requirements
* You must design a regional disaster recovery topology.
* The database backups have regulatory purposes and must be retained for seven years.
* CONT_SQL1 stores customers sales data that requires ETL operations for data analysis. A solution is required that reads data from SQL, performs ETL, and outputs to Power BI. The solution should use managed clusters to minimize costs. To optimize logistics, Contoso needs to analyze customer sales data to see if certain products are tied to specific times in the year.
* The analytics solution for customer sales data must be available during a regional outage.
Security and auditing
* Contoso requires all corporate computers to enable Windows Firewall.
* Azure servers should be able to ping other Contoso Azure servers.
* Employee PII must be encrypted in memory, in motion, and at rest. Any data encrypted by SQL Server must support equality searches, grouping, indexing, and joining on the encrypted data.
* Keys must be secured by using hardware security modules (HSMs).
* CONT_SQL3 must not communicate over the default ports
Cost
* All solutions must minimize cost and resources.
* The organization does not want any unexpected charges.
* The data engineers must set the SQL Data Warehouse compute resources to consume 300 DWUs.
* CONT_SQL2 is not fully utilized during non-peak hours. You must minimize resource costs for during non- peak hours.
Design for data security and compliance
Testlet 5
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
General Overview
ADatum Corporation is a medical company that has 5,000 physicians located in more than 300 hospitals across the US. The company has a medical department, a sales department, a marketing department, a medical research department, and a human resources department.
You are redesigning the application environment of ADatum.
Physical Locations
ADatum has three main offices in New York, Dallas, and Los Angeles. The offices connect to each other by using a WAN link. Each office connects directly to the Internet. The Los Angeles office also has a datacenter that hosts all the company's applications.
Existing Environment
Health Review
ADatum has a critical OLTP web application named Health Review that physicians use to track billing, patient care, and overall physician best practices.
Health Interface
ADatum has a critical application named Health Interface that receives hospital messages related to patient care and status updates. The messages are sent in batches by each hospital's enterprise relationship management (ERM) system by using a VPN. The data sent from each hospital can have varying columns and formats.
Currently, a custom C# application is used to send the data to Health Interface. The application uses deprecated libraries and a new solution must be designed for this functionality.
Health Insights
ADatum has a web-based reporting system named Health Insights that shows hospital and patient insights to physicians and business users. The data is created from the data in Health Review and Health Interface, as well as manual entries.
Database Platform
Currently, the databases for all three applications are hosted on an out-of-date VMware cluster that has a single instance of Microsoft SQL Server 2012.
Problem Statements
ADatum identifies the following issues in its current environment:
* Over time, the data received by Health Interface from the hospitals has slowed, and the number of messages has increased.
* When a new hospital joins ADatum, Health Interface requires a schema modification due to the lack of data standardization.
* The speed of batch data processing is inconsistent.
Business Requirements
Business Goals
ADatum identifies the following business goals:
* Migrate the applications to Azure whenever possible.
* Minimize the development effort required to perform data movement.
* Provide continuous integration and deployment for development, test, and production environments.
* Provide faster access to the applications and the data and provide more consistent application performance.
* Minimize the number of services required to perform data processing, development, scheduling, monitoring, and the operationalizing of pipelines.
Health Review Requirements
ADatum identifies the following requirements for the Health Review application:
* Ensure that sensitive health data is encrypted at rest and in transit.
* Tag all the sensitive health data in Health Review. The data will be used for auditing.
Health Interface Requirements
ADatum identifies the following requirements for the Health Interface application:
* Upgrade to a data storage solution that will provide flexible schemas and increased throughput for writing data. Data must be regionally located close to each hospital, and reads must display be the most recent committed version of an item.
* Reduce the amount of time it takes to add data from new hospitals to Health Interface.
* Support a more scalable batch processing solution in Azure.
* Reduce the amount of development effort to rewrite existing SQL queries.
Health Insights Requirements
ADatum identifies the following requirements for the Health Insights application:
* The analysis of events must be performed over time by using an organizational date dimension table.
* The data from Health Interface and Health Review must be available in Health Insights within 15 minutes of being committed.
* The new Health Insights application must be built on a massively parallel processing (MPP) architecture that will support the high performance of joins on large fact tables.
NEW QUESTION 18
You need to design the image processing and storage solutions.
What should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-service-tier-hyperscale
NEW QUESTION 19
You are designing a solution that will use Azure Databricks and Azure Data Lake Storage Gen2.
From Databricks, you need to access Data Lake Storage directly by using a service principal.
What should you include in the solution?
- A. access keys in Data Lake Storage
- B. shared access signatures (SAS) in Data Lake Storage
- C. an organizational relationship in Azure Active Directory (Azure AD)
- D. an application registration in Azure Active Directory (Azure AD)
Answer: D
Explanation:
Create and grant permissions to service principal
If your selected the access method requires a service principal with adequate permissions, and you do not have one, follow these steps:
1. Create an Azure AD application and service principal that can access resources. Note the following properties:
* client-id: An ID that uniquely identifies the application.
* directory-id: An ID that uniquely identifies the Azure AD instance.
* service-credential: A string that the application uses to prove its identity.
2. Register the service principal, granting the correct role assignment, such as Storage Blob Data
3. Contributor, on the Azure Data Lake Storage Gen2 account.
References:
https://docs.databricks.com/data/data-sources/azure/azure-datalake-gen2.html
NEW QUESTION 20
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.
Answer:
Explanation:
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 21
Which Azure service and feature should you recommend using to manage the transient data for Data Lake Storage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Scenario: Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use. Files that have a modified date that is older than 14 days must be removed.
Service: Azure Data Factory
Clean up files by built-in delete activity in Azure Data Factory (ADF).
ADF built-in delete activity, which can be part of your ETL workflow to deletes undesired files without writing code. You can use ADF to delete folder or files from Azure Blob Storage, Azure Data Lake Storage Gen1, Azure Data Lake Storage Gen2, File System, FTP Server, sFTP Server, and Amazon S3.
You can delete expired files only rather than deleting all the files in one folder. For example, you may want to only delete the files which were last modified more than 13 days ago.
Feature: Delete Activity
Reference:
https://azure.microsoft.com/sv-se/blog/clean-up-files-by-built-in-delete-activity-in-azure-data-factory/
NEW QUESTION 22
You use Azure Data Lake Storage Gen2 to store data that data scientists and data engineers will query by using Azure Databricks interactive notebooks. The folders in Data Lake Storage will be secured, and users will have access only to the folders that relate to the projects on which they work.
You need to recommend which authentication methods to use for Databricks and Data Lake Storage to provide the users with the appropriate access. The solution must minimize administrative effort and development effort Which authentication method should you recommend for each Azure service? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Databricks: Personal access tokens
To authenticate and access Databricks REST APIs, you use personal access tokens. Tokens are similar to passwords; you should treat them with care. Tokens expire and can be revoked.
Data Lake Storage: Azure Active Directory
Azure Data Lake Storage Gen1 uses Azure Active Directory for authentication.
References:
https://docs.azuredatabricks.net/dev-tools/api/latest/authentication.html
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lakes-store-authentication-using-azure-active-directory
NEW QUESTION 23
Inventory levels must be calculated by subtracting the current day's sales from the previous day's final inventory.
Which two options provide Litware with the ability to quickly calculate the current inventory levels by store and product? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Consume the output of the event hub by using Azure Stream Analytics and aggregate the data by store and product. Output the resulting data into Databricks. Calculate the inventory levels in Databricks and output the data to Azure Blob storage.
- B. Output Event Hubs Avro files to Azure Blob storage. Use Transact-SQL to calculate the inventory levels by using PolyBase in Azure SQL Data Warehouse.
- C. Output Event Hubs Avro files to Azure Blob storage. Trigger an Azure Data Factory copy activity to run every 10 minutes to load the data into Azure SQL Data Warehouse. Use Transact-SQL to aggregate the
- D. Consume the output of the event hub by using Azure Stream Analytics and aggregate the data by store and product. Output the resulting data directly to Azure SQL Data Warehouse. Use Transact-SQL to calculate the inventory levels.
- E. Consume the output of the event hub by using Databricks. Use Databricks to calculate the inventory levels and output the data to Azure SQL Data Warehouse.
Answer: C,D
Explanation:
data by store and product.
Explanation:
A: Azure Stream Analytics is a fully managed service providing low-latency, highly available, scalable complex event processing over streaming data in the cloud. You can use your Azure SQL Data Warehouse database as an output sink for your Stream Analytics jobs.
E: Event Hubs Capture is the easiest way to get data into Azure. Using Azure Data Lake, Azure Data Factory, and Azure HDInsight, you can perform batch processing and other analytics using familiar tools and platforms of your choosing, at any scale you need.
Note: Event Hubs Capture creates files in Avro format.
Captured data is written in Apache Avro format: a compact, fast, binary format that provides rich data structures with inline schema. This format is widely used in the Hadoop ecosystem, Stream Analytics, and Azure Data Factory.
Scenario: The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure.
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/sql-data-warehouse/sql-data-warehouse-integrate-azure-stream-analytics
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-capture-overview
NEW QUESTION 24
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. Azure Data Lake Store
- B. Blob Storage
- C. Azure Cosmos DB
- D. HDInsight
Answer: C
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
Reference:
https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview
NEW QUESTION 25
You are designing an enterprise data warehouse in Azure Synapse Analytics that will store website traffic analytic in a star schema.
You plan to have a fact table for website visits. The table will be approximately 5 GB.
You need to recommend which distribution type and index type to use for the table. The solution must provide the fastest query performance.
What should you recommend? 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/sql-data-warehouse/sql-data-warehouse-tables-distribute
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-index
NEW QUESTION 26
You have a data model that you plan to implement in an Azure SQL data warehouse as shown in the following exhibit.
All the dimension tables will be less than 5 GB after compression, and the fact table will be approximately 6 TB.
Which type of table should you use for each table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Replicated
Replicated tables are ideal for small star-schema dimension tables, because the fact table is often distributed on a column that is not compatible with the connected dimension tables. If this case applies to your schema, consider changing small dimension tables currently implemented as round-robin to replicated.
Box 2: Replicated
Box 3: Replicated
Box 4: Hash-distributed
For Fact tables use hash-distribution with clustered columnstore index. Performance improves when two hash tables are joined on the same distribution column.
References:
https://azure.microsoft.com/en-us/updates/reduce-data-movement-and-make-your-queries-more-efficient-with-th
https://azure.microsoft.com/en-us/blog/replicated-tables-now-generally-available-in-azure-sql-data-warehouse/
NEW QUESTION 27
You are planning a design pattern based on the Lambda architecture as shown in the exhibit.
Which Azure services should you use f2 or the cold path? To answer, drag the appropriate services to the correct layers. 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.
Answer:
Explanation:
Explanation
Layer 2: Azure Data Lake Storage Gen2
Layer 3: Azure SQL Data Warehouse
Azure SQL Data Warehouse can be used for batch processing.
Note: Lambda architectures use batch-processing, stream-processing, and a serving layer to minimize the latency involved in querying big data.
References:
https://azure.microsoft.com/en-us/blog/lambda-architecture-using-azure-cosmosdb-faster-performance-low-tco-l
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
NEW QUESTION 28
You have an Azure subscription that contains an Azure Data Lake Storage account. The storage account contains a data lake named DataLake1.
You plan to use an Azure data factory to ingest data from a folder in DataLake1, transform the data, and land the data in another folder.
You need to ensure that the data factory can read and write data from any folder in the DataLake1 file system.
The solution must meet the following requirements:
* Minimize the risk of unauthorized user access.
* Use the principle of least privilege.
* Minimize maintenance effort.
How should you configure access to the storage account for the data factory? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
Answer:
Explanation:
Explanation
Box 1: Azure Active Directory (Azure AD)
On Azure, managed identities eliminate the need for developers having to manage credentials by providing an identity for the Azure resource in Azure AD and using it to obtain Azure Active Directory (Azure AD) tokens.
Box 2: a managed identity
A data factory can be associated with a managed identity for Azure resources, which represents this specific data factory. You can directly use this managed identity for Data Lake Storage Gen2 authentication, similar to using your own service principal. It allows this designated factory to access and copy data to or from your Data Lake Storage Gen2.
Note: The Azure Data Lake Storage Gen2 connector supports the following authentication types.
* Account key authentication
* Service principal authentication
* Managed identities for Azure resources authentication
Reference:
https://docs.microsoft.com/en-us/azure/active-directory/managed-identities-azure-resources/overview
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-data-lake-storage
NEW QUESTION 29
You need to design the image processing solution to meet the optimization requirements for image tag data.
What should you configure? 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.
Answer:
Explanation:
Explanation
Tagging data must be uploaded to the cloud from the New York office location.
Tagging data must be replicated to regions that are geographically close to company office locations.
NEW QUESTION 30
You need to design a data architecture to bring together all your data at any scale and provide insights into all your users through the use of analytical dashboards, operational reports, and advanced analytics.
How should you complete the architecture? To answer, drag the appropriate Azure services to the correct locations in the architecture. 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.
Answer:
Explanation:
Explanation
Ingest: Azure Data Factory
Store: Azure Blob storage
Model & Serve: Azure SQL Data Warehouse
Load data into Azure SQL Data Warehouse.
Prep & Train: Azure Databricks.
Extract data from Azure Blob storage.
References:
https://docs.microsoft.com/en-us/azure/azure-databricks/databricks-extract-load-sql-data-warehouse
NEW QUESTION 31
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. No
- B. Yes
Answer: A
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 32
You are designing an application. You plan to use Azure SQL Database to support the application.
The application will extract data from the Azure SQL Database and create text documents. The text documents will be placed into a cloud-based storage solution. The text storage solution must be accessible from an SMB network share.
You need to recommend a data storage solution for the text documents.
Which Azure data storage type should you recommend?
- A. Table
- B. Files
- C. Queue
- D. Blob
Answer: B
Explanation:
Explanation
Azure Files enables you to set up highly available network file shares that can be accessed by using the standard Server Message Block (SMB) protocol.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-introduction
https://docs.microsoft.com/en-us/azure/storage/tables/table-storage-overview
NEW QUESTION 33
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