Updated Jan-2022 Pass DP-201 Exam - Real Practice Test Questions
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NEW QUESTION 121
You need to design storage for the solution.
Which storage services should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Images: Azure Data Lake Storage
Scenario: Image data must be stored in a single data store at minimum cost.
Customer data: Azure Blob Storage
Scenario: Customer data must be analyzed using managed Spark clusters.
Spark clusters in HDInsight are compatible with Azure Storage and Azure Data Lake Storage.
Azure Storage includes these data services: Azure Blob, Azure Files, Azure Queues, and Azure Tables.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-overview
NEW QUESTION 122
Which Azure service should you recommend for the analytical data store so that the business analysts and data scientists can execute ad hoc queries as quickly as possible?
- A. Azure SQL Data Warehouse
- B. Azure Data Lake Storage Gen2
- C. Azure SQL Database
- D. Azure Cosmos DB
Answer: B
Explanation:
Explanation
There are several differences between a data lake and a data warehouse. Data structure, ideal users, processing methods, and the overall purpose of the data are the key differentiators.
Scenario: Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
NEW QUESTION 123
A company stores large datasets in Azure, including sales transactions and customer account information.
You must design a solution to analyze the data. You plan to create the following HDInsight clusters:
You need to ensure that the clusters support the query requirements.
Which cluster types should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Interactive Query
Choose Interactive Query cluster type to optimize for ad hoc, interactive queries.
Box 2: Hadoop
Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process.
Note: In Azure HDInsight, there are several cluster types and technologies that can run Apache Hive queries.
When you create your HDInsight cluster, choose the appropriate cluster type to help optimize performance for your workload needs.
For example, choose Interactive Query cluster type to optimize for ad hoc, interactive queries. Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process. Spark and HBase cluster types can also run Hive queries.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/hdinsight-hadoop-optimize-hive-query?toc=%2Fko-kr%2F
NEW QUESTION 124
You need to design a solution to meet the SQL Server storage requirements for CONT_SQL3.
Which type of disk should you recommend?
- A. Premium SSD Managed Disk
- B. Ultra SSD Managed Disk
- C. Standard SSD Managed Disk
Answer: B
Explanation:
CONT_SQL3 requires an initial scale of 35000 IOPS.
Ultra SSD Managed Disk Offerings
The following table provides a comparison of ultra solid-state-drives (SSD) (preview), premium SSD, standard SSD, and standard hard disk drives (HDD) for managed disks to help you decide what to use.
Reference:
https://docs.microsoft.com/en-us/azure/virtual-machines/windows/disks-types
NEW QUESTION 125
You are designing a new application that uses Azure Cosmos DB. The application will support a variety of data patterns including log records and social media mentions.
You need to recommend which Cosmos DB API to use for each data pattern. The solution must minimize resource utilization.
Which API should you recommend for each data pattern? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Log records: SQL
Social media mentions: Gremlin
You can store the actual graph of followers using Azure Cosmos DB Gremlin API to create vertexes for each user and edges that maintain the "A-follows-B" relationships. With the Gremlin API, you can get the followers of a certain user and create more complex queries to suggest people in common. If you add to the graph the Content Categories that people like or enjoy, you can start weaving experiences that include smart content discovery, suggesting content that those people you follow like, or finding people that you might have much in common with.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/social-media-apps
NEW QUESTION 126
You are designing security for administrative access to Azure SQL Data Warehouse.
You need to recommend a solution to ensure that administrators use two-factor authentication when accessing the data warehouse from Microsoft SQL Server Management Studio (SSMS).
What should you include in the recommendation?
- A. Azure Active Directory (Azure AD) Privileged Identity Management (PIM)
- B. Azure conditional access policies
- C. Azure Active Directory (Azure AD) Identity Protection
- D. Azure Key Vault secrets
Answer: B
Explanation:
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-conditional-access
NEW QUESTION 127
A company has a real-time data analysis solution that is hosted on Microsoft Azure. The solution uses Azure Event Hub to ingest data and an Azure Stream Analytics cloud job to analyze the data. The cloud job is configured to use 120 Streaming Units (SU).
You need to optimize performance for the Azure Stream Analytics job.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Scale the SU count for the job down
- B. Implement event ordering
- C. Implement query parallelization by partitioning the data output
- D. Scale the SU count for the job up
- E. Implement query parallelization by partitioning the data output
- F. Implement Azure Stream Analytics user-defined functions (UDF)
Answer: D,E
Explanation:
Explanation
Scale out the query by allowing the system to process each input partition separately.
F: A Stream Analytics job definition includes inputs, a query, and output. Inputs are where the job reads the data stream from.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization
NEW QUESTION 128
You need to design the storage for the Health Insights data platform.
Which types of tables should you include in the design? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Hash-distributed tables
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.
Hash-distributed tables improve query performance on large fact tables.
Box 2: Round-robin distributed tables
A round-robin distributed table distributes table rows evenly across all distributions. The assignment of rows to distributions is random.
Scenario:
ADatum identifies the following requirements for the Health Insights application:
* 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.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
Topic 5, Data Engineer for Trey Research
Overview
You are a data engineer for Trey Research. The company is close to completing a joint project with the government to build smart highways infrastructure across North America. This involves the placement of sensors and cameras to measure traffic flow, car speed, and vehicle details.
You have been asked to design a cloud solution that will meet the business and technical requirements of the smart highway.
Solution components
Telemetry Capture
The telemetry capture system records each time a vehicle passes in front of a sensor. The sensors run on a custom embedded operating system and record the following telemetry data:
* Time
* Location in latitude and longitude
* Speed in kilometers per hour (kmph)
* Length of vehicle in meters
Visual Monitoring
The visual monitoring system is a network of approximately 1,000 cameras placed near highways that capture images of vehicle traffic every 2 seconds. The cameras record high resolution images. Each image is approximately 3 MB in size.
Requirements: Business
The company identifies the following business requirements:
* External vendors must be able to perform custom analysis of data using machine learning technologies.
* You must display a dashboard on the operations status page that displays the following metrics:
telemetry, volume, and processing latency.
* Traffic data must be made available to the Government Planning Department for the purpose of modeling changes to the highway system. The traffic data will be used in conjunction with other data such as information about events such as sporting events, weather conditions, and population statistics.
External data used during the modeling is stored in on-premises SQL Server 2016 databases and CSV files stored in an Azure Data Lake Storage Gen2 storage account.
* Information about vehicles that have been detected as going over the speed limit during the last 30
* minutes must be available to law enforcement officers. Several law enforcement organizations may respond to speeding vehicles.
* The solution must allow for searches of vehicle images by license plate to support law enforcement investigations. Searches must be able to be performed using a query language and must support fuzzy searches to compensate for license plate detection errors.
Requirements: Security
The solution must meet the following security requirements:
* External vendors must not have direct access to sensor data or images.
* Images produced by the vehicle monitoring solution must be deleted after one month. You must minimize costs associated with deleting images from the data store.
* Unauthorized usage of data must be detected in real time. Unauthorized usage is determined by looking for unusual usage patterns.
* All changes to Azure resources used by the solution must be recorded and stored. Data must be provided to the security team for incident response purposes.
Requirements: Sensor data
You must write all telemetry data to the closest Azure region. The sensors used for the telemetry capture system have a small amount of memory available and so must write data as quickly as possible to avoid losing telemetry data.
NEW QUESTION 129
You are planning a big data solution in Azure.
You need to recommend a technology that meets the following requirements:
* Be optimized for batch processing.
* Support autoscaling.
* Support per-cluster scaling.
Which technology should you recommend?
- A. Azure HDInsight with Spark
- B. Azure Databricks
- C. Azure Synapse Analytics
- D. Azure Analysis Services
Answer: B
Explanation:
Azure Databricks is an Apache Spark-based analytics platform. Azure Databricks supports autoscaling and manages the Spark cluster for you.
Incorrect Answers:
A, B:
NEW QUESTION 130
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.
Answer:
Explanation:
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels
NEW QUESTION 131
Which Azure Data Factory components should you recommend using together to import the customer data from Salesforce to Data Lake Storage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Self-hosted integration runtime
A self-hosted IR is capable of nunning copy activity between a cloud data stores and a data store in private network.
Box 2: Schedule trigger
Schedule every 8 hours
Box 3: Copy activity
Scenario:
* Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
NEW QUESTION 132
You are designing an application that will store petabytes of medical imaging data When the data is first created, the data will be accessed frequently during the first week. After one month, the data must be accessible within 30 seconds, but files will be accessed infrequently. After one year, the data will be accessed infrequently but must be accessible within five minutes.
You need to select a storage strategy for the data. The solution must minimize costs.
Which storage tier should you use for each time frame? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
First week: Hot
Hot - Optimized for storing data that is accessed frequently.
After one month: Cool
Cool - Optimized for storing data that is infrequently accessed and stored for at least 30 days.
After one year: Cool
NEW QUESTION 133
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. Replicated table
- B. External table
- C. Hash-distributed table
- D. Round-robin distributed table
Answer: D
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 134
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. Blob
- B. Table
- C. Queue
- D. Files
Answer: D
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 135
You discover that the highest chance of corruption or bad data occurs during nightly inventory loads.
You need to ensure that you can quickly restore the data to its state before the nightly load and avoid missing any streaming data.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation
Step 1: Before the nightly load, create a user-defined restore point
SQL Data Warehouse performs a geo-backup once per day to a paired data center. The RPO for a geo-restore is 24 hours. If you require a shorter RPO for geo-backups, you can create a user-defined restore point and restore from the newly created restore point to a new data warehouse in a different region.
Step 2: Restore the data warehouse to a new name on the same server.
Step 3: Swap the restored database warehouse name.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore
NEW QUESTION 136
You are planning a design pattern based on the Lambda architecture as shown in the exhibit.
Which Azure service should you use for the hot path?
- A. Azure Data Catalog
- B. Azure SQL Database
- C. Azure Synapse Analytics
- D. Azure Cosmos DB
Answer: D
Explanation:
In Azure, all of the following data stores will meet the core requirements supporting real-time processing:
* Apache Spark in Azure Databricks
* Azure Stream Analytics
* HDInsight with Spark Streaming
* HDInsight with Storm
* Azure Functions
* Azure App Service WebJobs
Note: Lambda architectures use batch-processing, stream-processing, and a serving layer to minimize the latency involved in querying big data.
Reference:
https://azure.microsoft.com/en-us/blog/lambda-architecture-using-azure-cosmosdb-faster-performance-low- tco-low-devops/
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/stream-processing
https://docs.microsoft.com/en-us/azure/cosmos-db/lambda-architecture
Design for data security and compliance
Testlet 1
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
Litware, Inc. owns and operates 300 convenience stores across the US. The company sells a variety of packaged foods and drinks, as well as a variety of prepared foods, such as sandwiches and pizzas.
Litware has a loyalty club whereby members can get daily discounts on specific items by providing their membership number at checkout.
Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
Requirements. Business Goals
Litware wants to create a new analytics environment in Azure to meet the following requirements:
* See inventory levels across the stores. Data must be updated as close to real time as possible.
* Execute ad hoc analytical queries on historical data to identify whether the loyalty club discounts increase sales of the discounted products.
* Every four hours, notify store employees about how many prepared food items to produce based on historical demand from the sales data.
Requirements. Technical Requirements
Litware identifies the following technical requirements:
* Minimize the number of different Azure services needed to achieve the business goals
* Use platform as a service (PaaS) offerings whenever possible and avoid having to provision virtual machines that must be managed by Litware.
* Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.
* Use Azure Active Directory (Azure AD) authentication whenever possible.
* Use the principle of least privilege when designing security.
* 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.
* Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
* Ensure that you can quickly restore a copy of the analytical data store within one hour in the event of corruption or accidental deletion.
Requirements. Planned Environment
Litware plans to implement the following environment:
* 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.
* Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Daily inventory data comes from a Microsoft SQL server located on a private network.
* Litware currently has 5 TB of historical sales data and 100 GB of customer data. The company expects approximately 100 GB of new data per month for the next year.
* Litware will build a custom application named FoodPrep to provide store employees with the calculation results of how many prepared food items to produce every four hours.
* Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.
NEW QUESTION 137
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