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NEW QUESTION 90
You need to design the storage for the visual monitoring system.
Which storage solution should you recommend?
- A. Azure SQL database
- B. Azure Media Services
- C. Azure Blob storage
- D. Azure Table storage
Answer: C
Explanation:
Azure Blobs: A massively scalable object store for text and binary data.
Scenario:
* 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.
* 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.
Incorrect Answers:
B: Azure Tables: A NoSQL store for schemaless storage of structured data.
D: Microsoft Azure Media Services (AMS) is a leading full-service media platform for securely delivering live and on-demand video to virtually any device.
Reference:
https://docs.microsoft.com/en-us/azure/storage/common/storage-introduction
NEW QUESTION 91
Inventory levels must be calculated by subtracting the current day's sales from the previous day's final inventory.
Which two options provide Litware with the ability to quickly calculate the current inventory levels by store and product? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Consume the output of the event hub by using Azure Stream Analytics and aggregate the data by store and product. Output the resulting data into Databricks. Calculate the inventory levels in Databricks and output the data to Azure Blob storage.
- B. Output Event Hubs Avro files to Azure Blob storage. Use Transact-SQL to calculate the inventory levels by using PolyBase in Azure SQL Data Warehouse.
- C. Output Event Hubs Avro files to Azure Blob storage. Trigger an Azure Data Factory copy activity to run every 10 minutes to load the data into Azure SQL Data Warehouse. Use Transact-SQL to aggregate the data by store and product.
- D. Consume the output of the event hub by using Azure Stream Analytics and aggregate the data by store and product. Output the resulting data directly to Azure SQL Data Warehouse. Use Transact-SQL to calculate the inventory levels.
- E. Consume the output of the event hub by using Databricks. Use Databricks to calculate the inventory levels and output the data to Azure SQL Data Warehouse.
Answer: C,D
Explanation:
A: Azure Stream Analytics is a fully managed service providing low-latency, highly available, scalable complex event processing over streaming data in the cloud. You can use your Azure SQL Data Warehouse database as an output sink for your Stream Analytics jobs.
E: Event Hubs Capture is the easiest way to get data into Azure. Using Azure Data Lake, Azure Data Factory, and Azure HDInsight, you can perform batch processing and other analytics using familiar tools and platforms of your choosing, at any scale you need.
Note: Event Hubs Capture creates files in Avro format.
Captured data is written in Apache Avro format: a compact, fast, binary format that provides rich data structures with inline schema. This format is widely used in the Hadoop ecosystem, Stream Analytics, and Azure Data Factory.
Scenario: The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure.
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/sql-data-warehouse/sql-data-warehouse-integrate-azure-stream-analytics
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-capture-overview
NEW QUESTION 92
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 plan to store delimited text files in an Azure Data Lake Storage account that will be organized into department folders.
You need to configure data access so that users see only the files in their respective department folder.
Solution: From the storage account, you disable a hierarchical namespace, and you use access control lists (ACLs).
Does this meet the goal?
- A. No
- B. Yes
Answer: B
Explanation:
Azure Data Lake Storage implements an access control model that derives from HDFS, which in turn derives from the POSIX access control model.
Blob container ACLs does not support the hierarchical namespace, so it must be disabled.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-known-issues
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-access-control
NEW QUESTION 93
You need to design the SensorData collection.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Explanation:
Box 1: Eventual
Traffic data insertion rate must be maximized.
Sensor data must be stored in a Cosmos DB named treydata in a collection named SensorData With Azure Cosmos DB, developers can choose from five well-defined consistency models on the consistency spectrum. From strongest to more relaxed, the models include strong, bounded staleness, session, consistent prefix, and eventual consistency.
Box 2: License plate
This solution reports on all data related to a specific vehicle license plate. The report must use data from the SensorData collection.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels
NEW QUESTION 94
You need to design the solution for the government planning department.
Which services should you include in the design?
- A. Azure SQL Data Warehouse and Elastic Queries
- B. Azure SQL Database and Polybase
- 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 95
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:
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 96
You are planning the deployment of two separate Azure Cosmos DB databases named db1 and db2.
You need to recommend a deployment strategy that meets the following requirements:
* Costs for both databases must be minimized.
* Db1 must meet an SLA of 99.99% for both reads and writes.
* Db2 must meet an SLA of 99.99% for writes and 99.999% for reads.
Which deployment strategy should you recommend for each database? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Db1: A single read/write region
Db2: A single write region and multi read regions
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/high-availability
NEW QUESTION 97
You need to design a solution that meets the business requirements of Health Insights.
What should you include in the recommendation?
- A. Azure Cosmos DB that uses the SQL API
- B. Azure Cosmos DB that uses the Gremlin
- C. Azure Data Factory
- D. Azure Databricks
Answer: D
Explanation:
Explanation
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 98
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 plan to store delimited text files in an Azure Data Lake Storage account that will be organized into department folders.
You need to configure data access so that users see only the files in their respective department folder.
Solution: From the storage account, you disable a hierarchical namespace, and you use RBAC.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Instead of RBAC use access control lists (ACLs).
Note: Azure Data Lake Storage implements an access control model that derives from HDFS, which in turn derives from the POSIX access control model.
Blob container ACLs does not support the hierarchical namespace, so it must be disabled.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-known-issues
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-access-control
NEW QUESTION 99
You plan to create a real-time monitoring app that alerts users when a device travels more than 200 meters away from a designated location.
You need to design an Azure Stream Analytics job to process the data for the planned app. The solution must minimize the amount of code developed and the number of technologies used.
What should you include in the Stream Analytics job? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Input type: Stream
You can process real-time IoT data streams with Azure Stream Analytics.
Input source: Azure IoT Hub
In a real-world scenario, you could have hundreds of these sensors generating events as a stream. Ideally, a gateway device would run code to push these events to Azure Event Hubs or Azure IoT Hubs.
Function: Geospatial
With built-in geospatial functions, you can use Azure Stream Analytics to build applications for scenarios such as fleet management, ride sharing, connected cars, and asset tracking.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-get-started-with-azure-stream-analytics
https://docs.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios
NEW QUESTION 100
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 101
You are designing an application that will store petabytes of medical imaging data When the data is first created, the data will be accessed frequently during the first week. After one month, the data must be accessible within 30 seconds, but files will be accessed infrequently. After one year, the data will be accessed infrequently but must be accessible within five minutes.
You need to select a storage strategy for the data. The solution must minimize costs.
Which storage tier should you use for each time frame? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
First week: Hot
Hot - Optimized for storing data that is accessed frequently.
After one month: Cool
Cool - Optimized for storing data that is infrequently accessed and stored for at least 30 days.
After one year: Cool
NEW QUESTION 102
You are designing a real-time processing solution for maintenance work requests that are received via email. The solution will perform the following actions:
Store all email messages in an archive.
Access weather forecast data by using the Python SDK for Azure Open Datasets.
Identify high priority requests that will be affected by poor weather conditions and store the requests in an Azure SQL database.
The solution must minimize costs.
How should you complete the solution? 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:
Reference:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-capture-overview
https://docs.microsoft.com/en-us/azure/connectors/connectors-create-api-azure-event-hubs
NEW QUESTION 103
You are planning a solution to aggregate streaming data that originates in Apache Kafka and is output to Azure Data Lake Storage Gen2. The developers who will implement the stream processing solution use Java.
Which service should you recommend using to process the streaming data?
- A. Azure Data Factory
- B. Azure Event Hubs
- C. Azure Stream Analytics
- D. Azure Databricks
Answer: D
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/stream-processing
NEW QUESTION 104
You have a large amount of sensor data stored in an Azure Data Lake Storage Gen2 account. The files are in the Parquet file format.
New sensor data will be published to Azure Event Hubs.
You need to recommend a solution to add the new sensor data to the existing sensor data in real-time. The solution must support the interactive querying of the entire dataset.
Which type of server should you include in the recommendation?
- A. Azure Databricks
- B. Azure Cosmos DB
- C. Azure Stream Analytics
- D. Azure SQL Database
Answer: C
Explanation:
Azure Stream Analytics is a fully managed PaaS offering that enables real-time analytics and complex event processing on fast moving data streams.
By outputting data in parquet format into a blob store or a data lake, you can take advantage of Azure Stream Analytics to power large scale streaming extract, transfer, and load (ETL), to run batch processing, to train machine learning algorithms, or to run interactive queries on your historical data.
Reference:
https://azure.microsoft.com/en-us/blog/new-capabilities-in-stream-analytics-reduce-development-time-for-big-data-apps/
NEW QUESTION 105
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