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Who should take the DP-201 exam
The Designing an Azure Data Solution DP-201 Exam certification is an internationally recognized validation that identifies persons who earn it as possessing skilled as a Microsoft Certified Azure Data Engineer Associate. If candidates want significant improvement in career growth needs enhanced knowledge, skills, and talents. The Designing an Azure Data Solution DP-201 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass Designing an Azure Data Solution DP-201 Exam then he should take this exam.
The Microsoft DP-201: Designing an Azure Data Solution exam is developed to validate the ability of the professionals to execute technical tasks, such as designing Azure data storage solutions, designing data processing solutions, and designing for data security & compliance. The test is specifically designed for those individuals who are looking to build a career in the Azure Data Solution domain. Passing this exam together with Microsoft DP-200: Implementing an Azure Data Solution takes the candidates closer to getting the Microsoft Certified: Azure Data Engineer Associate certification.
NEW QUESTION 49
You need to design the runtime environment for the Real Time Response system.
What should you recommend?
- A. Memory Optimized Nodes without the Enterprise Security package
- B. General Purpose nodes with the Enterprise Security package
- C. General Purpose nodes without the Enterprise Security package
- D. Memory Optimized nodes with the Enterprise Security package
Answer: A
Explanation:
Scenario: You must maximize the performance of the Real Time Response system.
Design data processing solutions
Question Set 5
NEW QUESTION 50
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-directo
NEW QUESTION 51
You need to recommend a solution for storing customer data. What should you recommend?
- A. Azure SQL Data Warehouse
- B. Azure Databricks
- C. Azure Stream Analytics
- D. Azure SQL Database
Answer: B
Explanation:
From the scenario:
Customer data must be analyzed using managed Spark clusters.
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data.
References:
https://www.microsoft.com/developerblog/2019/01/18/running-parallel-apache-spark-notebook-workloads-on-azure-databricks/
NEW QUESTION 52
You are planning a design pattern based on the Kappa architecture as shown in the exhibit.
Which Azure service should you use for each layer? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Layer 1: Azure Data Factory
Layer 2: Azure Databricks
Azure Databricks is fully integrated with Azure Data Factory .
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/
NEW QUESTION 53
You design data engineering solutions for a company.
You must integrate on-premises SQL Server data into an Azure solution that performs Extract-Transform-Load (ETL) operations have the following requirements:
* Develop a pipeline that can integrate data and run notebooks.
* Develop notebooks to transform the data.
* Load the data into a massively parallel processing database for later analysis.
You need to recommend a solution.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION 54
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:
Explanation
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-import
NEW QUESTION 55
You have data on the 75,000 employees of your company. The data contains the properties shown in the following table.
You need to store the employee data in an Azure Cosmos DB container. Most queries on the data will filter by the Current Department and the Employee Surname properties.
Which partition key and item ID should you use for the container? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Partition key: Current Department
Item ID: Employee ID
References:
https://docs.microsoft.com/en-us/rest/api/storageservices/designing-a-scalable-partitioning-strategy-for-azure-table-storage
NEW QUESTION 56
You are developing a solution that performs real-time analysis of IoT data in the cloud.
The solution must remain available during Azure service updates.
You need to recommend a solution.
Which two actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Deploy an Azure Stream Analytics job to two separate regions that are not in a pair.
- B. Monitor jobs in the primary region for failure.
- C. Monitor jobs in both regions for failure.
- D. Deploy an Azure Stream Analytics job to one region in a paired region.
- E. Deploy an Azure Stream Analytics job to each region in a paired region.
Answer: C,E
Explanation:
Stream Analytics guarantees jobs in paired regions are updated in separate batches. As a result there is a sufficient time gap between the updates to identify potential breaking bugs and remediate them.
Customers are advised to deploy identical jobs to both paired regions.
In addition to Stream Analytics internal monitoring capabilities, customers are also advised to monitor the jobs as if both are production jobs. If a break is identified to be a result of the Stream Analytics service update, escalate appropriately and fail over any downstream consumers to the healthy job output. Escalation to support will prevent the paired region from being affected by the new deployment and maintain the integrity of the paired jobs.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-reliability
NEW QUESTION 57
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 58
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 Factory
- B. Azure Databricks
- C. Azure Database for PostgreSQL
- D. Azure SQL Database
Answer: B
Explanation:
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.
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/stream-processing
NEW QUESTION 59
You need to ensure that performance requirements for Backtrack reports are met.
What should you recommend? To answer, drag the appropriate technologies to the correct locations. Each technology may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Cosmos DB indexes
The report for Backtrack must execute as quickly as possible.
You can override the default indexing policy on an Azure Cosmos container, this could be useful if you want to tune the indexing precision to improve the query performance or to reduce the consumed storage.
Box 2: Cosmos DB TTL
This solution reports on all data related to a specific vehicle license plate. The report must use data from the SensorData collection. Users must be able to filter vehicle data in the following ways:
* vehicles on a specific road
* vehicles driving above the speed limit
Note: With Time to Live or TTL, Azure Cosmos DB provides the ability to delete items automatically from a container after a certain time period. By default, you can set time to live at the container level and override the value on a per-item basis. After you set the TTL at a container or at an item level, Azure Cosmos DB will automatically remove these items after the time period, since the time they were last modified.
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
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 60
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
NEW QUESTION 61
You are designing a solution to process data from multiple Azure event hubs in near real-time.
Once processed, the data will be written to an Azure SQL database.
The solution must meet the following requirements:
* Support the auditing of resource and data changes.
* Support data versioning and rollback.
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: Azure Stream Analytics
Users can now ingest, process, view, and analyze real-time streaming data into a table directly from a database in Azure SQL Database. They do so in the Azure portal using Azure Stream Analytics.
In the Azure portal, you can select an events source (Event Hub/IoT Hub), view incoming real-time events, and select a table to store events.
Stream Analytics leverages versioning of reference data to augment streaming data with the reference data that was valid at the time the event was generated. This ensures repeatability of results.
Box 2: Replay
Reference data is versioned, enabling to always get the same results, even when we "replay" the stream.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/stream-data-stream-analytics-integration
https://azure.microsoft.com/en-us/updates/additional-support-for-managed-identity-and-new-features-in-azure-st
NEW QUESTION 62
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:
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 63
You are designing an Azure Databricks interactive cluster. The cluster will be used infrequently and will be configured for auto-termination.
You need to ensure that the cluster configuration is retained indefinitely after the cluster is terminated. The solution must minimize costs.
What should you do?
- A. Create an Azure runbook that starts the cluster every 90 days.
- B. Terminate the cluster manually when processing completes.
- C. Clone the cluster after it is terminated.
- D. Pin the cluster.
Answer: D
Explanation:
To keep an interactive cluster configuration even after it has been terminated for more than 30 days, an administrator can pin a cluster to the cluster list.
References:
https://docs.azuredatabricks.net/clusters/clusters-manage.html#automatic-termination
NEW QUESTION 64
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 65
Your company is an online retailer that can have more than 100 million orders during a 24-hour period, 95 percent of which are placed between 16:30 and 17:00. All the orders are in US dollars. The current product line contains the following three item categories:
* Games with 15,123 items
* Books with 35,312 items
* Pens with 6,234 items
You are designing an Azure Cosmos DB data solution for a collection named Orders Collection. The following documents is a typical order in Orders Collection.
Order Collection is expected to have a balanced read/write-intensive workload.
Which partition key provides the most efficient throughput?
- A. Item/Currency
- B. Item/Category
- C. OrderTime
- D. Item/id
Answer: B
Explanation:
Explanation
Choose a partition key that has a wide range of values and access patterns that are evenly spread across logical partitions. This helps spread the data and the activity in your container across the set of logical partitions, so that resources for data storage and throughput can be distributed across the logical partitions.
Choose a partition key that spreads the workload evenly across all partitions and evenly over time. Your choice of partition key should balance the need for efficient partition queries and transactions against the goal of distributing items across multiple partitions to achieve scalability.
Candidates for partition keys might include properties that appear frequently as a filter in your queries. Queries can be efficiently routed by including the partition key in the filter predicate.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/partitioning-overview#choose-partitionkey
NEW QUESTION 66
You are designing a recovery strategy for your Azure SQL Databases.
The recovery strategy must use default automated backup settings. The solution must include a Point-in time restore recovery strategy.
You need to recommend which backups to use and the order in which to restore backups.
What should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
References:
https://azure.microsoft.com/sv-se/blog/azure-sql-database-point-in-time-restore/
NEW QUESTION 67
Which Azure Data Factory components should you recommend using together to import the daily inventory data from SQL 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.
Scenario: Daily inventory data comes from a Microsoft SQL server located on a private network.
Box 2: Schedule trigger
Daily schedule
Box 3: Copy activity
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.
NEW QUESTION 68
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 69
You are designing an Azure Databricks interactive cluster.
You need to ensure that the cluster meets the following requirements:
Enable auto-termination
Retain cluster configuration indefinitely after cluster termination.
What should you recommend?
- A. Terminate the cluster manually at process completion.
- B. Pin the cluster
- C. Clone the cluster after it is terminated.
- D. Start the cluster after it is terminated.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
To keep an interactive cluster configuration even after it has been terminated for more than 30 days, an administrator can pin a cluster to the cluster list.
References:
https://docs.azuredatabricks.net/user-guide/clusters/terminate.html
NEW QUESTION 70
You are designing an Azure Data Factory pipeline for processing data. The pipeline will process data that is stored in general-purpose standard Azure storage.
You need to ensure that the compute environment is created on-demand and removed when the process is completed.
Which type of activity should you recommend?
- A. Data Lake Analytics U-SQL activity
- B. Databricks Jar activity
- C. Databricks Python activity
- D. HDInsight Pig activity
Answer: D
Explanation:
The HDInsight Pig activity in a Data Factory pipeline executes Pig queries on your own or on-demand HDInsight cluster.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/transform-data-using-hadoop-pig
NEW QUESTION 71
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