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The content of the Microsoft DP-201 exam revolves around three main topics that comprise of specific knowledge and skills that the candidates should develop before sitting for the test. The details of these areas are outlined below:
Topic 1. Designing Azure Data Storage Solutions (40-45%)
- Designing relational Cloud data stores: this subtopic focuses on such abilities as designing data partitions and distribution; designing for scale (comprising latency & throughput); designing a solution that utilizes Azure Synapse Analytics; designing a strategy for disaster recovery; designing for high availability.
- Suggesting an Azure data storage solution in compliance with given requirements: this requires one’s skills in choosing the proper data storage solution in order to satisfy the technical & business requirements; choosing the type of partition distribution.
- Designing non-relational Cloud data stores: here the applicants should demonstrate that they are capable of designing data partitions and distribution; designing for scale (latency, throughput, and multi-region); designing a solution that utilizes Data Lake Storage Gen2, Blob storage, or Cosmos DB; selecting the proper Cosmos DB API; designing a strategy for disaster recovery; designing for high availability.
NEW QUESTION 23
You need to design the data loading pipeline for Planning Assistance.
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.
Answer:
Explanation:
Explanation
Box 1: SqlSink Table
Sensor data must be stored in a Cosmos DB named treydata in a collection named SensorData Box 2: Cosmos Bulk Loading Use Copy Activity in Azure Data Factory to copy data from and to Azure Cosmos DB (SQL API).
Scenario: Data from the Sensor Data collection will automatically be loaded into the Planning Assistance database once a week by using Azure Data Factory. You must be able to manually trigger the data load process.
Data used for Planning Assistance must be stored in a sharded Azure SQL Database.
References:
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-cosmos-db
Topic 2, Case study 1The 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.
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.
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 question on 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 sections 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 on 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 button to return to the question.
Overview
You develop data engineering solutions for Graphics Design Institute, a global media company with offices in New York City, Manchester, Singapore, and Melbourne.
The New York office hosts SQL Server databases that stores massive amounts of customer data. The company also stores millions of images on a physical server located in the New York office. More than 2 TB of image data is added each day. The images are transferred from customer devices to the server in New York.
Many images have been placed on this server in an unorganized manner, making it difficult for editors to search images. Images should automatically have object and color tags generated. The tags must be stored in a document database, and be queried by SQL You are hired to design a solution that can store, transform, and visualize customer data.
Requirements
Business
The company identifies the following business requirements:
* You must transfer all images and customer data to cloud storage and remove on-premises servers.
* You must develop an analytical processing solution for transforming customer data.
* You must develop an image object and color tagging solution.
* Capital expenditures must be minimized.
* Cloud resource costs must be minimized.
Technical
The solution has the following technical requirements:
* 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.
* Image data must be stored in a single data store at minimum cost.
* Customer data must be analyzed using managed Spark clusters.
* Power BI must be used to visualize transformed customer data.
* All data must be backed up in case disaster recovery is required.
Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support:
* parallel processing of customer data
* hyper-scale storage of images
* global region data replication of processed image data
NEW QUESTION 24
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-low-devops/
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
NEW QUESTION 25
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 26
You need to design the authentication and authorization methods for sensors.
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:
Sensor data must be stored in a Cosmos DB named treydata in a collection named SensorData Sensors must have permission only to add items to the SensorData collection Box 1: Resource Token Resource tokens provide access to the application resources within a Cosmos DB database.
Enable clients to read, write, and delete resources in the Cosmos DB account according to the permissions they've been granted.
Box 2: Cosmos DB user
You can use a resource token (by creating Cosmos DB users and permissions) when you want to provide access to resources in your Cosmos DB account to a client that cannot be trusted with the master key.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/secure-access-to-data
NEW QUESTION 27
You are designing the security for a mission critical Azure SQL database named DB1. DB1 contains several columns that store Personally Identifiable Information (PII) data You need to recommend a security solution that meets the following requirements:
* Ensures that DB1 is encrypted at rest
* Ensures that data from the columns containing PII data is encrypted in transit Which security solution should you recommend for DB1 and the columns? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
DB1: Transparent Data Encryption
Azure SQL Database currently supports encryption at rest for Microsoft-managed service side and client-side encryption scenarios.
Support for server encryption is currently provided through the SQL feature called Transparent Data Encryption.
Columns: Always encrypted
Always Encrypted is a feature designed to protect sensitive data stored in Azure SQL Database or SQL Server databases. Always Encrypted allows clients to encrypt sensitive data inside client applications and never reveal the encryption keys to the database engine (SQL Database or SQL Server).
Note: Most data breaches involve the theft of critical data such as credit card numbers or personally identifiable information. Databases can be treasure troves of sensitive information. They can contain customers' personal data (like national identification numbers), confidential competitive information, and intellectual property. Lost or stolen data, especially customer data, can result in brand damage, competitive disadvantage, and serious fines--even lawsuits.
References:
https://docs.microsoft.com/en-us/azure/security/fundamentals/encryption-atrest
https://docs.microsoft.com/en-us/azure/security/fundamentals/database-security-overview
NEW QUESTION 28
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.
Answer:
Explanation:
Explanation:
Scenario:
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.
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
Reference:
https://docs.microsoft.com/en-us/azure/azure-databricks/what-is-azure-databricks
NEW QUESTION 29
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 30
A company manufactures automobile parts. The company installs IoT sensors on manufacturing machinery.
You must design a solution that analyzes data from the sensors.
You need to recommend a solution that meets the following requirements:
Data must be analyzed in real-time.
Data queries must be deployed using continuous integration.
Data must be visualized by using charts and graphs.
Data must be available for ETL operations in the future.
The solution must support high-volume data ingestion.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Develop an Azure Stream Analytics application that queries the data and outputs to Power BI. Use Azure Pipelines to deploy the Azure Stream Analytics application.
- B. Use Azure Analysis Services to query the data. Output query results to Power BI.
- C. Develop an Azure Stream Analytics application that queries the data and outputs to Power BI. Use Azure Data Factory to deploy the Azure Stream Analytics application.
- D. Develop an application that sends the IoT data to an Azure Event Hub.
- E. Configure an Azure Event Hub to capture data to Azure Data Lake Storage.
- F. Develop an application that sends the IoT data to an Azure Data Lake Storage container.
Answer: C,D,E
NEW QUESTION 31
You have a MongoDB database that you plan to migrate to an Azure Cosmos DB account that uses the MongoDB API.
During testing, you discover that the migration takes longer than expected.
You need to recommend a solution that will reduce the amount of time it takes to migrate the data.
What are two possible recommendations to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Increase the Request Units (RUs).
- B. Add a write region.
- C. Create unique indexes.
- D. Turn off indexing.
- E. Create compound indexes.
Answer: A,D
Explanation:
A: Increase the throughput during the migration by increasing the Request Units (RUs).
For customers that are migrating many collections within a database, it is strongly recommend to configure database-level throughput. You must make this choice when you create the database. The minimum database- level throughput capacity is 400 RU/sec. Each collection sharing database-level throughput requires at least
100 RU/sec.
B: By default, Azure Cosmos DB indexes all your data fields upon ingestion. You can modify the indexing policy in Azure Cosmos DB at any time. In fact, it is often recommended to turn off indexing when migrating data, and then turn it back on when the data is already in Cosmos DB.
Reference:
https://docs.microsoft.com/bs-latn-ba/Azure/cosmos-db/mongodb-pre-migration
NEW QUESTION 32
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
Topic 3, Case study 2
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 question on 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 sections 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 on this case study, click the 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 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.
NEW QUESTION 33
You manage an on-premises server named Server1 that has a database named Database1. The company purchases a new application that can access data from Azure SQL Database.
You recommend a solution to migrate Database1 to an Azure SQL Database instance.
What should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION 34
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 35
You need to design the solution for the government planning department.
Which services should you include in the design?
- A. Azure SQL Database and Polybase
- B. Azure SQL Data Warehouse and Elastic Queries
- C. Azure SQL Data Warehouse and Polybase
- D. Azure SQL Database and Elastic Queries
Answer: C
Explanation:
PolyBase is a new feature in SQL Server 2016. It is used to query relational and non-relational databases (NoSQL) such as CSV files.
Scenario: 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.
Reference:
https://www.sqlshack.com/sql-server-2016-polybase-tutorial/
Topic 6, Litware Case
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 36
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 37
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.
Answer:
Explanation:
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=sql-server-2017
https://docs.microsoft.com/en-us/azure/security/azure-security-encryption-atrest
NEW QUESTION 38
Which Azure data storage solution should you recommend for each application? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Health Review: Azure SQL Database
Scenario: 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: Azure Cosmos DB
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: Azure SQL Data Warehouse
Azure SQL Data Warehouse is a cloud-based enterprise data warehouse that leverages massively parallel processing (MPP) to quickly run complex queries across petabytes of data. Use SQL Data Warehouse as a key component of a big data solution.
You can access Azure SQL Data Warehouse (SQL DW) from Databricks using the SQL Data Warehouse connector (referred to as the SQL DW connector), a data source implementation for Apache Spark that uses Azure Blob Storage, and PolyBase in SQL DW to transfer large volumes of data efficiently between a Databricks cluster and a SQL DW instance.
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.databricks.com/data/data-sources/azure/sql-data-warehouse.html
NEW QUESTION 39
You are designing a Spark job that performs batch processing of daily web log traffic.
When you deploy the job in the production environment, it must meet the following requirements:
* Run once a day.
* Display status information on the company intranet as the job runs.
You need to recommend technologies for triggering and monitoring jobs.
Which technologies 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.
Answer:
Explanation:
Explanation
Box 1: Livy
You can use Livy to run interactive Spark shells or submit batch jobs to be run on Spark.
Box 2: Beeline
Apache Beeline can be used to run Apache Hive queries on HDInsight. You can use Beeline with Apache Spark.
Note: Beeline is a Hive client that is included on the head nodes of your HDInsight cluster. Beeline uses JDBC to connect to HiveServer2, a service hosted on your HDInsight cluster. You can also use Beeline to access Hive on HDInsight remotely over the internet.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-livy-rest-interface
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-use-hive-beeline
NEW QUESTION 40
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. Use an Azure Stream Analytics job in the cloud. Ingress data from the Azure Event Hub instance and
build queries that output to Power BI. - B. Use an Azure Stream Analytics job on an edge device. Ingress data from an Azure Data Factory
instance and build queries that output to Power BI. - C. Send data from the application to Azure Data Lake Storage.
- D. Send data from the application to an Azure Stream Analytics job.
- E. Use an Azure Stream Analytics job in the cloud. Ingress data from an Azure Event Hub instance and
build queries that output to Azure Data Lake Storage. - F. Send data from the application to an Azure Event Hub instance.
Answer: A,F
Explanation:
Explanation/Reference:
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
DP-201
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 question
on 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 sections 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 on 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
Trey Research is a technology innovator. The company partners with regional transportation department
office to build solutions that improve traffic flow and safety.
The company is developing the following solutions:
Regional transportation departments installed traffic sensor systems on major highways across North
America. Sensors record the following information each time a vehicle passes in front of a sensor:
Time
Location in latitude and longitude
Speed in kilometers per second (kmps)
License plate number
Length of vehicle in meters
Sensors provide data by using the following structure:
Traffic sensors will occasionally capture an image of a vehicle for debugging purposes.
You must optimize performance of saving/storing vehicle images.
Traffic sensor data
Sensors must have permission only to add items to the SensorData collection.
Traffic data insertion rate must be maximized.
Once every three months all traffic sensor data must be analyzed to look for data patterns that indicate
sensor malfunctions.
Sensor data must be stored in a Cosmos DB named treydata in a collection named SensorData
The impact of vehicle images on sensor data throughout must be minimized.
Backtrack
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
Planning Assistance
Data used for Planning Assistance must be stored in a sharded Azure SQL Database.
Data from the Sensor Data collection will automatically be loaded into the Planning Assistance database
once a week by using Azure Data Factory. You must be able to manually trigger the data load process.
Privacy and security policy
Azure Active Directory must be used for all services where it is available.
For privacy reasons, license plate number information must not be accessible in Planning Assistance.
Unauthorized usage of the Planning Assistance data must be detected as quickly as possible.
Unauthorized usage is determined by looking for an unusual pattern of usage.
Data must only be stored for seven years.
Performance and availability
The report for Backtrack must execute as quickly as possible.
The SLA for Planning Assistance is 70 percent, and multiday outages are permitted.
All data must be replicated to multiple geographic regions to prevent data loss.
You must maximize the performance of the Real Time Response system.
Financial requirements
Azure resource costs must be minimized where possible.
NEW QUESTION 41
You are designing a data processing solution that will run as a Spark job on an HDInsight cluster. The solution will be used to provide near real-time information about online ordering for a retailer.
The solution must include a page on the company intranet that displays summary information.
The summary information page must meet the following requirements:
* Display a summary of sales to date grouped by product categories, price range, and review scope.
* Display sales summary information including total sales, sales as compared to one day ago and sales as compared to one year ago.
* Reflect information for new orders as quickly as possible.
You need to recommend a design for the solution.
What should you recommend? To answer, select the appropriate configuration in the answer area.
Answer:
Explanation:
Explanation
Box 1: DataFrame
DataFrames
Best choice in most situations.
Provides query optimization through Catalyst.
Whole-stage code generation.
Direct memory access.
Low garbage collection (GC) overhead.
Not as developer-friendly as DataSets, as there are no compile-time checks or domain object programming.
Box 2: parquet
The best format for performance is parquet with snappy compression, which is the default in Spark 2.x.
Parquet stores data in columnar format, and is highly optimized in Spark.
NEW QUESTION 42
......
DP-201 Dumps PDF and Test Engine Exam Questions: https://www.exam4pdf.com/DP-201-dumps-torrent.html
