Microsoft 70-475 Online Practice Questions and Exam Preparation

Microsoft 70-475 Online Questions & Answers

• Question 81:

  You have a Microsoft Azure SQL database that contains Personally Identifiable Information (PII).

  To mitigate the PII risk, you need to ensure that data is encrypted while the data is at rest. The solution must minimize any changes to front-end applications.

  What should you use?

  A. Transport Layer Security (TLS)
  B. transparent data encryption (TDE)
  C. a shared access signature (SAS)
  D. the ENCRYPTBYPASSPHRASE T-SQL function
  B. transparent data encryption (TDE)

  ---

  Transparent data encryption (TDE) helps protect Azure SQL Database, Azure SQL Managed Instance, and Azure Data Warehouse against the threat of malicious activity. It performs real-time encryption and decryption of the database, associated backups, and transaction log files at rest without requiring changes to the application.

  References: https://docs.microsoft.com/en-us/azure/sql-database/transparent-data-encryption-azure-sql

• Question 82:

  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 HDInsight cluster.

  Does this meet the goal?

  A. Yes
  B. No
  B. No

  ---

  HDInsight cluster billing starts once a cluster is created and stops when the cluster is deleted. Billing is pro-rated per minute, so you should always delete your cluster when it is no longer in use. Reference: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-provision-linux-clusters

• Question 83:

  Your company plans to deploy a web application that will display marketing data to its customers.

  You create an Apache Hadoop cluster in Microsoft Azure HDInsight and an Azure data factory.

  You need to implement a linked service to the cluster.

  Which JSON specification should you use to create the linked service?

  A. { "name":"AzureBlobOutput", "properties": { "type":"AzureBlob", "linkedServiceName":"StorageLinkedService", "typeProperties": { "folderPath":"adfgetstarted/partitioneddata", "format": { "type":"TextFormat", "columnDeliminater":"," } } "availability":" { "frequency":"Month", "interval": 1 } } }
  B. { "name":"HDInsightOnDemandLinkedService", "properties": { "type":"HDInsightOnDemand", "typeProperties": { "version":"3.2", "clusterSize": 1, "timeToLive":"00:30:00", "linkedServiceName":"StorageLinkedService" } } } {
  C. "name":"StorageLinkedService", "properties": { "type":"AzureStorage", "description": "", "typeProperties": { "connectionString": "DefaultEndpointProtocol=https;AccountName=; AccountKey=" } } } {
  D. "name":"AzureBlobInput", "properties": { "type":"AzureBlob", "linkedServiceName":"StorageLinkedService", "typeProperties": { "folderPath":"adfgetstarted/inputdata", "format": { "type":"TextFormat", "columnDeliminater":"," } } "availability":" { "frequency":"Month", "interval": 1 }, "external":true, "policy":{} } }
  B. { "name":"HDInsightOnDemandLinkedService", "properties": { "type":"HDInsightOnDemand", "typeProperties": { "version":"3.2", "clusterSize": 1, "timeToLive":"00:30:00", "linkedServiceName":"StorageLinkedService" } } } {

• Question 84:

  You need to recommend a platform architecture for a big data solution that meets the following requirements: Supports batch processing Provides a holding area for a 3-petabyte (PB) dataset Minimizes the development effort to implement the solution Provides near real-time relational querying across a multi-terabyte (TB) dataset

  Which two platform architectures should you include in the recommendation? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

  A. a Microsoft Azure SQL data warehouse
  B. a Microsoft Azure HDInsight Hadoop cluster
  C. a Microsoft SQL Server database
  D. a Microsoft Azure HDInsight Storm cluster
  E. Microsoft Azure Table Storage
  A. a Microsoft Azure SQL data warehouse
  E. Microsoft Azure Table Storage

  ---

  A: Azure SQL Data Warehouse is a SQL-based, fully-managed, petabyte-scale cloud data warehouse. It's highly elastic, and it enables you to set up in minutes and scale capacity in seconds. Scale compute and storage independently, which allows you to burst compute for complex analytical workloads, or scale down your warehouse for archival scenarios, and pay based on what you're using instead of being locked into predefined cluster configurations--and get more cost efficiency versus traditional data warehouse solutions.

  E: Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores--on-premises or cloud-based--Table storage lets you scale up without having to manually shard your dataset. Perform OData-based queries.

  Reference: https://azure.microsoft.com/en-us/services/sql-data-warehouse/ https://azure.microsoft.com/en-us/services/storage/tables/

• Question 85:

  DRAG DROP

  You are designing a data-driven data flow in Microsoft Azure Data Factory to copy data from Azure Blob storage to Azure SQL Database.

  You need to create the copy activity.

  How should you complete the JSON code? To answer, drag the appropriate code elements to the correct targets. Each element 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:

  

  

  ---

  In the typeProperties section, BlobSource is specified as the source type and SqlSink is specified as the sink type. Box 1: BlobSource

  Box 2: SqlSink

  References: https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipelines-activities

• Question 86:

  HOTSPOT

  You have the following script.

  CREATE TABLE UserVisits (username string, url string, time date)

  STORED AS TEXTFILE LOCATION "wasb:///Logs";

  CREATE TABLE UserVisitsOrc (username string, url string, time date)

  STORED AS ORC;

  INSERT INTO TABLE UserVisitsOrc SELECT * FROM UserVisits

  Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the script.

  NOTE: Each correct selection is worth one point.

  Hot Area:

  

  

  ---

  A table created without the EXTERNAL clause is called a managed table because Hive manages its data. Reference: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL

• Question 87:

  HOTSPOT

  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 configure the alert to meet the requirements for ETL.

  Which settings should you use for the alert? To answer, select the appropriate options in the answer area.

  NOTE: Each correct selection is worth one point.

  Hot Area:

  

  

• Question 88:

  DRAG DROP

  You manage a Microsoft Azure HDInsight Hadoop cluster. All of the data for the cluster is stored in Azure Premium Storage.

  You need to prevent all users from accessing the data directly. The solution must allow only the HDInsight service to access the data.

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

  Select and Place:

  

  

  ---

  Example: scenario where a customer wishes to explore a move from an existing Hortonworks (HDP) cluster to an Azure HDInsight (HDI) cluster. With the target Storage account in place, I can now configure the HDP cluster to connect to it. The easiest way I have found to do this is using Ambari: Login to the Ambari portal and navigate to the (default) dashboard Select HDFS from the left-hand navigation On the resulting HDFS page, click on the Configs tab On the resulting page, select the Advanced option Scroll down and expand the Custom core-site node Select Add Property... from the bottom of the expanded node Enter fs.azure.account.key..blob.core.windows.net, substituting the name of the Storage account for , as the Name of the property Enter the Account key as the Value of the property Click the Add button and verify the new property appears under the Custom core-site node Locate the notification bar at the top of the current page Click the Save button on the notification bar to push changes to the cluster Follow any remaining prompts to complete the Save process Once the Save process is completed, Ambari will indicate a restart of some services is required. Click the Restart button and Restart All Affected from the resulting drop-down. Follow any remaining prompts and monitor the process until it is successfully completed.

  Reference: https://blogs.msdn.microsoft.com/data_otaku/2016/12/09/pushing-data-from-a-hortonworks-cluster-to-an-azure-hdinsight-cluster/

• Question 89:

  You need to recommend a data analysis solution for 20,000 Internet of Things (IoT) devices. The solution must meet the following requirements:

  Each device must be identified by using its own credentials.

  Each device must be able to route data to multiple endpoints.

  The solution must require the minimum amount of customized code.

  What should you recommend?

  A. Microsoft Azure Notification Hubs
  B. Microsoft Azure IoT Hub
  C. Microsoft Azure Service Bus
  D. Microsoft Azure Event Hubs
  B. Microsoft Azure IoT Hub

  ---

  IoT Hub gives you a secure communication channel for your devices to send data.

  Per-device authentication enables each device to connect securely to IoT Hub and for each device to be managed securely.

  Azure IoT Hub has built-in message routing functionality that gives you flexibility to set up automatic rules-based message fan-out:

  Use message routing to control where your hub sends device telemetry.

  There is no additional cost to route messages to multiple endpoints.

  No-code routing rules take the place of custom message dispatcher code.

  References:

  https://docs.microsoft.com/en-us/azure/iot-hub/about-iot-hub

• Question 90:

  DRAG DROP

  You have data generated by sensors. The data is sent to Microsoft Azure Event Hubs.

  You need to have an aggregated view of the data in near real time by using five-minute tumbling windows to identify short-term trends. You must also have hourly and a daily aggregated views of the data.

  Which technology should you use for each task? To answer, drag the appropriate technologies to the correct tasks. Each technology may be used once, more than once, or not at all. You may need to drag the spilt bar between panes or scroll

  to view content.

  NOTE: Each correct selection is worth one point.

  Select and Place:

  

  

  ---

  Box 1: Azure HDInsight MapReduce

  Azure Event Hubs allows you to process massive amounts of data from websites, apps, and devices. The Event Hubs spout makes it easy to use Apache Storm on HDInsight to analyze this data in real time.

  Box 2: Azure Event Hub

  Box 3: Azure Stream Analytics

  Stream Analytics is a new service that enables near real time complex event processing over streaming data. Combining Stream Analytics with Azure Event Hubs enables near real time processing of millions of events per second. This

  enables you to do things such as augment stream data with reference data and output to storage (or even output to another Azure Event Hub for additional processing).

  Reference:

  https://blogs.msdn.microsoft.com/kaevans/2015/02/26/using-stream-analytics-with-event-hubs/

  https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-storm-develop-csharp-event-hub-topology