Microsoft 70-475 Online Practice Questions and Exam Preparation

Microsoft 70-475 Online Questions & Answers

• Question 61:

  You are building a streaming data analysis solution that will process approximately 1 TB of data weekly.

  You plan to use Microsoft Azure Stream Analytics to create alerts on real-time data. The data must be preserved for deeper analysis at a later date.

  You need to recommend a storage solution for the alert data. The solution must meet the following requirements:

  Support scaling up without any downtime

  Minimize data storage costs.

  What should you recommend using to store the data?

  A. Azure Data Lake
  B. Azure SQL Database
  C. Azure SQL Data Warehouse
  D. Apache Kafka
  A. Azure Data Lake

• Question 62:

  Overview:

  Litware, Inc. is a company that manufactures personal devices to track physical activity and other health-related data.

  Litware has a health tracking application that sends health-related data from a user's personal device to Microsoft Azure.

  Litware has three development and commercial offices. The offices are located in the United States, Luxembourg, and India.

  Litware products are sold worldwide. Litware has commercial representatives in more than 80 countries.

  Existing Environment:

  In addition to using desktop computers in all of the offices, Litware recently started using Microsoft Azure resources and services for both development and operations.

  Litware has an Azure Machine Learning solution.

  Litware recently extended its platform to provide third-party companies with the ability to upload data from devices to Azure. The data can be aggregated across multiple devices to provide users with a comprehensive view of their global

  health activity.

  While the upload from each device is small, potentially more than 100 million devices will upload data daily by using an Azure event hub. Each health activity has a small amount of data, such as activity type, start date/time, and end date/time.

  Each activity is limited to a total of 3 KB and includes a customer identification key.

  In addition to the Litware health tracking application, the users' activities can be reported to Azure by using an open API.

  The developers at Litware perform Machine Learning experiments to recommend an appropriate health activity based on the past three activities of a user.

  The Litware developers train a model to recommend the best activity for a user based on the hour of the day.

  Requirements:

  Litware plans to extend the existing dashboard features so that health activities can be compared between the users based on age, gender, and geographic region.

  Minimize the costs associated with transferring data from the event hub to Azure Storage.

  Litware identifies the following technical requirements:

  Data from the devices must be stored for three years in a format that enables the fast processing of date fields and filtering.

  The third-party companies must be able to use the Litware Machine Learning models to generate recommendations to their users by using a third-party application.

  Any changes to the health tracking application must ensure that the Litware developers can run the experiments without interrupting or degrading the performance of the production environment.

  Activity tracking data must be available to all of the Litware developers for experimentation. The developers must be prevented from accessing the private information of the users.

  When the Litware health tracking application asks users how they feel, their responses must be reported to Azure.

  You need to recommend a data transfer solution to support the business goals.

  What should you recommend?

  A. Configure the health tracking application to cache data locally for 24 hours.
  B. Configure the health tracking application to aggregate activities in blocks of 128 KB.
  C. Configure the health tracking application to cache data locally for 12 hours.
  D. Configure the health tracking application to aggregate activities in blocks of 64 KB.
  D. Configure the health tracking application to aggregate activities in blocks of 64 KB.

  ---

  From scenario:

  Minimize the costs associated with transferring data from the event hub to Azure Storage.

  Each activity is limited to a total of 3 KB and includes a customer identification key.

• Question 63:

  You have a Microsoft Azure Data Factory that loads data to an analytics solution.

  You receive an alert that an error occurred during the last processing of a data stream.

  You debug the problem and solve an error.

  You need to process the data stream that caused the error.

  What should you do?

  A. From Azure Cloud Shell, run the az dla job command.
  B. From Azure Cloud Shell, run the az batch job enable command.
  C. From PowerShell, run the Resume-AzureRmDataFactoryPipeline cmdlet.
  D. From PowerShell, run the Set-AzureRmDataFactorySliceStatus cmdlet.
  D. From PowerShell, run the Set-AzureRmDataFactorySliceStatus cmdlet.

  ---

  ADF operates on data in batches known as slices. Slices are obtained by querying data over a date-time window--for example, a slice may contain data for a specific hour, day, or week. References: https://blogs.msdn.microsoft.com/bigdatasupport/2016/08/31/rerunning-many-slices-and-activities-in-azure-data-factory/

• Question 64:

  Overview:

  Litware, Inc. is a company that manufactures personal devices to track physical activity and other health-related data.

  Litware has a health tracking application that sends health-related data from a user's personal device to Microsoft Azure.

  Litware has three development and commercial offices. The offices are located in the United States, Luxembourg, and India.

  Litware products are sold worldwide. Litware has commercial representatives in more than 80 countries.

  Existing Environment:

  In addition to using desktop computers in all of the offices, Litware recently started using Microsoft Azure resources and services for both development and operations.

  Litware has an Azure Machine Learning solution.

  Litware recently extended its platform to provide third-party companies with the ability to upload data from devices to Azure. The data can be aggregated across multiple devices to provide users with a comprehensive view of their global

  health activity.

  While the upload from each device is small, potentially more than 100 million devices will upload data daily by using an Azure event hub. Each health activity has a small amount of data, such as activity type, start date/time, and end date/time.

  Each activity is limited to a total of 3 KB and includes a customer identification key.

  In addition to the Litware health tracking application, the users' activities can be reported to Azure by using an open API.

  The developers at Litware perform Machine Learning experiments to recommend an appropriate health activity based on the past three activities of a user.

  The Litware developers train a model to recommend the best activity for a user based on the hour of the day.

  Requirements:

  Litware plans to extend the existing dashboard features so that health activities can be compared between the users based on age, gender, and geographic region.

  Minimize the costs associated with transferring data from the event hub to Azure Storage.

  Litware identifies the following technical requirements:

  Data from the devices must be stored for three years in a format that enables the fast processing of date fields and filtering.

  The third-party companies must be able to use the Litware Machine Learning models to generate recommendations to their users by using a third-party application.

  Any changes to the health tracking application must ensure that the Litware developers can run the experiments without interrupting or degrading the performance of the production environment.

  Activity tracking data must be available to all of the Litware developers for experimentation. The developers must be prevented from accessing the private information of the users.

  When the Litware health tracking application asks users how they feel, their responses must be reported to Azure.

  You need to recommend a data handling solution to support the planned changes to the dashboard.

  What is the best recommendation to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.

  A. anonymization
  B. encryption
  C. obfuscation
  D. compression
  C. obfuscation

  ---

  From scenario: Litware plans to extend the existing dashboard features so that health activities can be compared between the users based on age, gender, and geographic region. The developers must be prevented from accessing the private information of the users.

  Dynamic Data Masking can be used to hide or obfuscate sensitive data, by controlling how the data appears in the output of database queries. Dynamic Data Masking rules can be defined on particular columns, indicating how the data in those columns will appear when queried. There are no physical changes to the data in the database itself; the data remains intact and is fully available to authorized users or applications. Database operations remain unaffected, and the masked data has the same data type as the original data, so DDM can often be applied without making any changes to database procedures or application code.

  Reference: https://blogs.technet.microsoft.com/dataplatforminsider/2016/01/25/use-dynamic-data-masking-to-obfuscate-your-sensitive-data/

• Question 65:

  Note: The 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.

  Your company has multiple databases that contain millions of sales transactions.

  You plan to implement a data mining solution to identify purchasing fraud.

  You need to design a solution that mines 10 terabytes (TB) of sales date. The solution must meet the following requirements:

  Run the analysis to identify fraud once per week.

  Continue to receive new sales transactions while the analysis runs.

  Be able to stop computing services when the analysis is NOT running.

  Solution: You create a Microsoft Azure Data Lake job.

  Does this meet the goal?

  A. Yes
  B. No
  B. No

• Question 66:

  You have structured data that resides in Microsoft Azure Blob storage.

  You need to perform a rapid interactive analysis of the data and to generate visualizations of the data.

  What is the best type of Azure HDInsight cluster to use to achieve the goal? More than one answer choice may achieve the goal. Choose the BEST answer.

  A. Apache Storm
  B. Apache HBase
  C. Apache Hadoop
  D. Apache Spark
  D. Apache Spark

  ---

  A Spark cluster provides in-memory processing, interactive queries, micro-batch stream processing-

  Reference: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-provision-linux-clusters

• Question 67:

  DRAG DROP

  You are creating a retail analytics system for a company that manufactures equipment.

  The company manufactures thousands of IoT devices that report their status over the Internet.

  You need to recommend a solution to visualize notifications from the devices on a mobile-read dashboard.

  Which three actions should you recommend be performed in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

  Select and Place:

  

  

  ---

  References: https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-live-data-visualization-in-power-bi

• Question 68:

  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

  the 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 implement a new data warehouse.

  You have the following information regarding the data warehouse:

  The first data files for the data warehouse will be available in a few days.

  Most queries that will be executed against the data warehouse are ad-hoc.

  The schemas of data files that will be loaded to the data warehouse change often.

  One month after the planned implementation, the data warehouse will contain 15 TB of data.

  You need to recommend a database solution to support the planned implementation.

  Solution: You recommend an Apache Spark system.

  Does this meet the goal?

  A. Yes
  B. No
  B. No

• Question 69:

  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

  the 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 have an Apache Spark system that contains 5 TB of data.

  You need to write queries that analyze the data in the system. The queries must meet the following requirements:

  Use static data typing.

  Execute queries as quickly as possible.

  Have access to the latest language features.

  Solution: You write the queries by using Scala.

  A. Yes
  B. No
  A. Yes

• Question 70:

  DRAG DROP

  Overview:

  Relecloud is a social media company that processes hundreds of millions of social media posts per day and sells advertisements to several hundred companies. Relecloud has a Microsoft SQL Server database named DB1 that stores

  information about the advertisers. DB1 is hosted on a Microsoft Azure virtual machine.

  Relecloud has two main offices. The offices are located in San Francisco and New York City.

  The offices connect to each other by using a site-to-site VPN. Each office connects directly to the Internet.

  Relecloud modifies the pricing of its advertisements based on trending topics. Topics are considered to be trending if they generate many mentions in a specific country during a 15-minute time frame. The highest trending topics generate the

  highest advertising revenue.

  Relecloud wants to deliver reports to the advertisers by using Microsoft Power BI. The reports will provide real-time data on trending topics, current advertising rates, and advertising costs for a given month. Relecloud will analyze the trending

  topics data, and then store the data in a new data warehouse for ad-hoc analysis. The data warehouse is expected to grow at a rate of 1 GB per hour or 8.7 terabytes (TB) per year. The data will be retained for five years for the purpose of

  long-term trending.

  Requirements:

  Management at Relecloud must be able to view which topics are trending to adjust advertising rates in near real-time.

  Relecloud plans to implement a new streaming analytics platform that will report on trending topics.

  Relecloud plans to implement a data warehouse named DB2.

  Relecloud identifies the following technical requirements:

  Social media data must be analyzed to identify trending topics in real-time.

  The use of Infrastructure as a Service (IaaS) platforms must minimized, whenever possible.

  The real-time solution used to analyze the social media data must support scaling up and down without service interruption.

  Relecloud identifies the following technical requirements for the advertisers:

  The advertisers must be able to see only their own data in the Power BI reports.

  The advertisers must authenticate to Power BI by using Azure Active Directory (Azure AD) credentials.

  The advertisers must be able to leverage existing Transact-SQL language knowledge when developing the real-time streaming solution.

  Members of the internal advertising sales team at Relecloud must be able to see only the sales date of the advertisers to which they are assigned.

  The internal Relecloud advertising sales team must be prevented from inserting, updating, and deleting rows for the advertisers to which they are not assigned.

  The internal Relecloud advertising sales team must be able to use a text file to update the list of advertisers, and then to upload the file to Azure Blob storage.

  Relecloud identifies the following requirements for DB1:

  Data generated by the streaming analytics platform must be stored in DB1.

  The user names of the advertisers must be mapped to CustomerID in a table named Table2.

  The advertisers in DB1 must be stored in a table named Table1 and must be refreshed nightly.

  The user names of the employees at Relecloud must be mapped to EmployeeID in a table named Table3.

  Relecloud identifies the following requirements for DB2:

  DB2 must have minimal storage costs.

  DB2 must run load processes in parallel.

  DB2 must support massive parallel processing.

  DB2 must be able to store more than 40 TB of data.

  DB2 must support scaling up and down, as required.

  Data from DB1 must be archived in DB2 for long-term storage.

  All of the reports that are executed from DB2 must use aggregation.

  Users must be able to pause DB2 when the data warehouse is not in use.

  Users must be able to view previous versions of the data in DB2 by using aggregates.

  Relecloud identifies the following requirements for extract, transformation, and load (ETL):

  Data movement between DB1 and DB2 must occur each hour.

  An email alert must be generated when a failure of any type occurs during ETL processing.

  Sample code and data:

  You execute the following code for a table named rls_table1.

  

  You use the following code to create Table1.

  create table table1 (customerid int, salespersonid int ... ) Go

  The following is a sample of the streaming data.

  

  You need to create a query that identifies the trending topics.

  How should you complete the query? To answer, drag the appropriate values to the correct targets. Each value 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.

  Select and Place: