2021 DP-201 Question Bank: Free PDF Download Recently Updated Questions
DP-201 Certification Exam Dumps with 207 Practice Test Questions
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This exam measures your ability to accomplish the following technical tasks: design Azure data storage solutions; design data processing solutions; and design for data security and compliance.
NEW QUESTION 45
You need to recommend an Azure SQL Database pricing tier for Planning Assistance.
Which pricing tier should you recommend?
- A. Business critical Azure SQL Database single database
- B. General purpose Azure SQL Database single database
- C. Business critical Azure SQL Database Managed Instance
- D. General purpose Azure SQL Database Managed Instance
Answer: D
Explanation:
Azure resource costs must be minimized where possible.
Data used for Planning Assistance must be stored in a sharded Azure SQL Database.
The SLA for Planning Assistance is 70 percent, and multiday outages are permitted.
NEW QUESTION 46
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 47
You need to design the image processing and storage solutions.
What should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-service-tier-hyperscale
NEW QUESTION 48
You are designing a solution for the ad hoc analysis of data in Azure Databricks notebooks. The data will be stored in Azure Blob storage.
You need to ensure that Blob storage will support the recovery of the data if the data is overwritten accidentally.
What should you recommend?
- A. Add a resource lock.
- B. Use read-access geo-redundant storage (RA-GRS).
- C. Enable diagnostics logging.
- D. Enable soft delete.
Answer: D
Explanation:
Explanation
Soft delete protects blob data from being accidentally or erroneously modified or deleted. When soft delete is enabled for a storage account, blobs, blob versions (preview), and snapshots in that storage account may be recovered after they are deleted, within a retention period that you specify.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/soft-delete-overview
NEW QUESTION 49
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 50
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure SQL Database that will use elastic pools. You plan to store data about customers in a table. Each record uses a value for CustomerID.
You need to recommend a strategy to partition data based on values in CustomerID.
Proposed Solution: Separate data into customer regions by using vertical partitioning.
Does the solution meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation
Vertical partitioning is used for cross-database queries. Instead we should use Horizontal Partitioning, which also is called charding.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-query-overview
NEW QUESTION 51
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:
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 52
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 53
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 both regions for failure.
- C. Deploy an Azure Stream Analytics job to one region in a paired region.
- D. Monitor jobs in the primary region for failure.
- E. Deploy an Azure Stream Analytics job to each region in a paired region.
Answer: B,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 54
You plan to use an Azure SQL data warehouse to store the customer dat
a. You need to recommend a disaster recovery solution for the data warehouse. What should you include in the recommendation?
- A. AzCopy
- B. Geo-Redundant backups
- C. Read-only replicas
- D. AdICopy
Answer: B
Explanation:
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore
Topic 3, 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.
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 55
You need to ensure that security policies for the unauthorized detection system are met.
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: Blob storage
Configure blob storage for audit logs.
Scenario: 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 used for Planning Assistance must be stored in a sharded Azure SQL Database.
Box 2: Web Apps
SQL Advanced Threat Protection (ATP) is to be used.
One of Azure's most popular service is App Service which enables customers to build and host web applications in the programming language of their choice without managing infrastructure. App Service offers auto-scaling and high availability, supports both Windows and Linux. It also supports automated deployments from GitHub, Visual Studio Team Services or any Git repository. At RSA, we announced that Azure Security Center leverages the scale of the cloud to identify attacks targeting App Service applications.
References:
https://azure.microsoft.com/sv-se/blog/azure-security-center-can-identify-attacks-targeting-azure-app-service-applications/
NEW QUESTION 56
You are designing a highly available Azure Data Lake Storage solution that will include geo-zone-redundant storage (GZRS).
You need to monitor for replication delays that can affect the recovery point objective (RPO).
What should you include in the monitoring solution?
- A. Average Success E2E Latency
- B. availability
- C. 5xx: Server Error errors
- D. Last Sync Time
Answer: D
Explanation:
It's important to note that account failover often results in some data loss, because geo-replication always involves latency. The secondary endpoint is typically behind the primary endpoint. So, when you initiate a failover, any data that has not yet been replicated to the secondary region will be lost.
We [Microsoft] recommend that you always check the Last Sync Time property before initiating a failover to evaluate how far the secondary is behind the primary.
Incorrect Answers:
B: Success E2E Latency: The end-to-end latency of successful requests made to a storage service or the specified API operation, in milliseconds. This value includes the required processing time within Azure Storage to read the request, send the response, and receive acknowledgment of the response.
Reference:
https://azure.microsoft.com/en-us/blog/account-failover-now-in-public-preview-for-azure-storage/
https://docs.microsoft.com/en-us/azure/azure-monitor/essentials/metrics-supported
NEW QUESTION 57
A company has many applications. Each application is supported by separate on-premises databases.
You must migrate the databases to Azure SQL Database. You have the following requirements:
* Organize databases into groups based on database usage.
* Define the maximum resource limit available for each group of databases.
You need to recommend technologies to scale the databases to support expected increases in demand.
What should you recommend?
- A. Database sharding
- B. Elastic pools
- C. Read scale-out
- D. Managed instances
Answer: B
Explanation:
SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands. The databases in an elastic pool are on a single Azure SQL Database server and share a set number of resources at a set price.
You can configure resources for the pool based either on the DTU-based purchasing model or the vCore- based purchasing model.
Incorrect Answers:
D: Database sharding is a type of horizontal partitioning that splits large databases into smaller components, which are faster and easier to manage.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-pool
NEW QUESTION 58
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 Database
- B. Azure SQL Data Warehouse
- C. Azure Data Lake Storage Gen2
- D. Azure Cosmos DB
Answer: C
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 59
A company purchases IoT devices to monitor manufacturing machinery. The company uses an IoT appliance to communicate with the IoT devices.
The company must be able to monitor the devices in real-time.
You need to design the solution.
What should you recommend?
- A. Azure Analysis Services using Azure PowerShell
- B. Azure Data Factory instance using Azure Portal
- C. Azure Analysis Services using Azure Portal
- D. Azure Stream Analytics cloud job using Azure PowerShell
Answer: D
Explanation:
Explanation
Stream Analytics is a cost-effective event processing engine that helps uncover real-time insights from devices, sensors, infrastructure, applications and data quickly and easily.
Monitor and manage Stream Analytics resources with Azure PowerShell cmdlets and powershell scripting that execute basic Stream Analytics tasks.
Reference:
https://cloudblogs.microsoft.com/sqlserver/2014/10/29/microsoft-adds-iot-streaming-analytics-data-production-a
NEW QUESTION 60
You are designing a solution that will use Azure Table storage. The solution will log records in the following entity.
You are evaluating which partition key to use based on the following two scenarios:
* Scenario1: Minimize hotspots under heavy write workloads.
* Scenario2: Ensure that date lookups are as efficient as possible for read workloads.
Which partition key should you use for each scenario? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
References:
https://docs.microsoft.com/en-us/rest/api/storageservices/designing-a-scalable-partitioning-strategy-for-azure-table-storage
NEW QUESTION 61
You need to recommend a solution for storing customer data. What should you recommend?
- A. Azure SQL Database
- B. Azure SQL Data Warehouse
- C. Azure Databricks
- D. Azure Stream Analytics
Answer: C
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 62
You have an on-premises data warehouse that includes the following fact tables. Both tables have the following columns: DataKey, ProductKey, RegionKey. There are 120 unique product keys and 65 unique region keys.
Queries that use the data warehouse take a long time to complete.
You plan to migrate the solution to use Azure SQL Data Warehouse. You need to ensure that the Azure-based solution optimizes query performance and minimizes processing skew.
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: Hash-distributed
Box 2: ProductKey
ProductKey is used extensively in joins.
Hash-distributed tables improve query performance on large fact tables.
Box 3: Round-robin
Box 4: RegionKey
Round-robin tables are useful for improving loading speed.
Consider using the round-robin distribution for your table in the following scenarios:
* When getting started as a simple starting point since it is the default
* If there is no obvious joining key
* If there is not good candidate column for hash distributing the table
* If the table does not share a common join key with other tables
* If the join is less significant than other joins in the query
* When the table is a temporary staging table
Note: A distributed table appears as a single table, but the rows are actually stored across 60 distributions. The rows are distributed with a hash or round-robin algorithm.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
NEW QUESTION 63
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
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 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
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 64
What should you recommend as a batch processing solution for Health Interface?
- A. Azure Data Factory
- B. Azure CycleCloud
- C. Azure Stream Analytics
- D. Azure Databricks
Answer: C
Explanation:
Scenario: ADatum identifies the following requirements for the Health Interface application:
Support a more scalable batch processing solution in Azure.
Reduce the amount of time it takes to add data from new hospitals to Health Interface.
Data Factory integrates with the Azure Cosmos DB bulk executor library to provide the best performance when you write to Azure Cosmos DB.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-cosmos-db Design data processing solutions Testlet 5 Case study This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
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.
Design data processing solutions
Testlet 6
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, a SaaS application, 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 65
You are evaluating data storage solutions to support a new application.
You need to recommend a data storage solution that represents data by using nodes and relationships in graph structures.
Which data storage solution should you recommend?
- A. Azure Cosmos DB
- B. Azure Data Lake Store
- C. HDInsight
- D. Blob Storage
Answer: A
Explanation:
For large graphs with lots of entities and relationships, you can perform very complex analyses very quickly.
Many graph databases provide a query language that you can use to traverse a network of relationships efficiently.
Relevant Azure service: Cosmos DB
Reference:
https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview
NEW QUESTION 66
You have an Azure subscription that contains a logical Microsoft SQL server named Server1. Server1 hosts an Azure Synapse Analytics SQL dedicated pool named Pool1. You need to recommend a Transparent Data Encryption (TDE) solution for Server1. The solution must meet the following requirements:
* Track the usage of encryption keys.
* Maintain the access of client apps to Pool1 in the event of an Azure datacenter outage that affects the availability of the encryption keys.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
NEW QUESTION 67
You need to recommend the appropriate storage and processing solution?
What should you recommend?
- A. Flush the blob cache using Windows PowerShell.
- B. Configure the reading speed using Azure Data Studio.
- C. Enable auto-shrink on the database.
- D. Enable Apache Spark RDD (RDD) caching.
- E. Enable Databricks IO (DBIO) caching.
Answer: D
Explanation:
Explanation/Reference:
Explanation:
Scenario: 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.
Databricks File System (DBFS) is a distributed file system installed on Azure Databricks clusters. Files in
DBFS persist to Azure Blob storage, so you won't lose data even after you terminate a cluster.
The Databricks Delta cache, previously named Databricks IO (DBIO) caching, accelerates data reads by
creating copies of remote files in nodes' local storage using a fast intermediate data format. The data is
cached automatically whenever a file has to be fetched from a remote location. Successive reads of the
same data are then performed locally, which results in significantly improved reading speed.
References:
https://docs.databricks.com/delta/delta-cache.html#delta-cache
Question Set 4
NEW QUESTION 68
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