Real 70-475 Braindumps 2021

NEW QUESTION 1
You are developing an Apache Storm application by using Microsoft Visual Studio. You need to implement a custom topology that uses a custom bolt. Which type of object should you initialize in the main class?

• A. Stream
• B. TopologyBuilder
• C. Streamlnfo
• D. Logger

Answer: A

NEW QUESTION 2
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 identity 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 split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation: 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).

NEW QUESTION 3
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 states 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

Answer: A

NEW QUESTION 4
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 states 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 Python.

• A. Yes
• B. No

Answer: B

NEW QUESTION 5
You need to recommend a permanent Azure Storage solution for the activity data. The solution must meet the technical requirements.
What is the best recommendation to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.

• A. Azure SQL Database
• B. Azure Queue storage
• C. Azure Blob storage
• D. Azure Event Hubs

Answer: A

NEW QUESTION 6
You need to ingest data from various data stores into a Microsoft Azure SQL data warehouse by using PolyBase.
You create an Azure Data Factory.
Which three components should you create next? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

• A. an Azure Function
• B. datasets
• C. a pipeline
• D. an Azure Batch account
• E. linked services

Answer: AE

NEW QUESTION 7
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. Select the BEST answer.

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

Answer: D

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

NEW QUESTION 8
You are designing a solution for an Internet of Things (IoT) project.
You need to recommend a data storage solution for the project. The solution must meet the following
requirements:
Allow data to be queried in real-time as it streams into the solution
Provide the lowest amount of latency for loading data into the solution. What should you include in the recommendation?

• A. a Microsoft Azure SQL database that has In-Memory OLTP enabled
• B. a Microsoft Azure HDInsight Hadoop cluster
• C. a Microsoft Azure HDInsight R Server cluster
• D. a Microsoft Azure Table Storage solution

Answer: A

Explanation: References:
https://azure.microsoft.com/en-gb/blog/in-memory-oltp-in-azure-sql-database/

NEW QUESTION 9
You are planning a solution that will have multiple data files stored in Microsoft Azure Blob storage every hour. Data processing will occur once a day at midnight only.
You create an Azure data factory that has blob storage as the input source and an Azure HD Insight activity that uses the input to create an output Hive table.
You need to identify a data slicing strategy for the data factory.
What should you identify? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION 10
You plan to deploy a storage solution to store the output of stream analytics. You plan to store the data for the following three types of data streams:
Unstructured JSON data
Exploratory analytics
Pictures
You need to implement a storage solution for the data stream types.
Which storage solution should you implement for each data stream type? To answer, drag the appropriate storage solutions to the correct data stream types. Each storage solution may be used once, more than once, or not at all. You may need to drag the split bar between the panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation: Box 1: Azure Data Lake Store
Stream Analytics supports Azure Data Lake Store. Azure Data Lake Store is an enterprise-wide hyper-scale repository for big data analytic workloads. Data Lake Store enables you to store data of any size, type and ingestion speed for operational and exploratory analytics. Stream Analytics has to be authorized to access the Data Lake Store.
Box 2: Azure Cosmos DB
Stream Analytics can target Azure Cosmos DB for JSON output, enabling data archiving and low-latency queries on unstructured JSON data.
Box 3: Azure Blob Storage
Blob storage offers a cost-effective and scalable solution for storing large amounts of unstructured data in the cloud.
Incorrect Asnwers: Azure SQL Database:
Azure SQL Database can be used as an output for data that is relational in nature or for applications that depend on content being hosted in a relational database. Stream Analytics jobs write to an existing table in an Azure SQL Database.
Azure Service Bus Queue:
Service Bus Queues offer a First In, First Out (FIFO) message delivery to one or more competing consumers. Typically, messages are expected to be received and processed by the receivers in the temporal order in which they were added to the queue, and each message is received and processed by only one message consumer.
Azure Table Storage
Azure Table storage offers highly available, massively scalable storage, so that an application can automatically scale to meet user demand. Table storage is Microsoft’s NoSQL key/attribute store, which one can leverage for structured data with fewer constraints on the schema. Azure Table storage can be used to store data for persistence and efficient retrieval.
References: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs

NEW QUESTION 11
You plan to create a Microsoft Azure Data Factory pipeline that will connect to an Azure HDInsight cluster that uses Apache Spark.
You need to recommend which file format must be used by the pipeline. The solution must meet the following requirements:
Store data in the columnar format
Support compression
Which file format should you recommend?

• A. XML
• B. AVRO
• C. text
• D. Parquet

Answer: D

Explanation: Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language.
Apache Parquet supports compression.

NEW QUESTION 12
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 tor 12 hours.
• D. Configure the health tracking application to aggregate activities in blocks of 64 KB.

Answer: D

NEW QUESTION 13
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 a Microsoft Azure deployment that contains the following services:
Azure Data Lake
Azure Cosmos DB
Azure Data Factory
Azure SQL Database
You load several types of data to Azure Data Lake.
You need to load data from Azure SQL Database to Azure Data Lake. Solution: You use the AzCopy utility.
Does this meet the goal?

• A. Yes
• B. No

Answer: B

Explanation: Note: You can use the Copy Activity in Azure Data Factory to copy data to and from Azure Data Lake Storage Gen1 (previously known as Azure Data Lake Store). Azure SQL database is supported as source.
References: https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-data-lake-store

NEW QUESTION 14
You have the following script.

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.

Answer:

Explanation: A table created without the EXTERNAL clause is called a managed table because Hive manages its data.

NEW QUESTION 15
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

Answer: AE

Explanation: 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.

NEW QUESTION 16
You have an Apache Hive cluster in Microsoft Azure HDInsight. The cluster contains 10 million data files. You plan to archive the data.
The data will be analyzed monthly.
You need to recommend a solution to move and store the data. The solution must minimize how long it takes to move the data and must minimize costs.
Which two services should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A. Azure Queue storage
• B. Microsoft SQL Server Integration Services (SSIS)
• C. Azure Table Storage
• D. Azure Data Lake
• E. Azure Data Factory

Answer: DE

Explanation: D: To analyze data in HDInsight cluster, you can store the data either in Azure Storage, Azure Data Lake Storage Gen 1/Azure Data Lake Storage Gen 2, or both. Both storage options enable you to safely delete HDInsight clusters that are used for computation without losing user data.
E: The Spark activity in a Data Factory pipeline executes a Spark program on your own or on-demand HDInsight cluster. It handles data transformation and the supported transformation activities.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-use-data-lake-store https://docs.microsoft.com/en-us/azure/data-factory/transform-data-using-spark

NEW QUESTION 17
You are designing a partitioning scheme for ingesting real-time data by using Kafka. Kafka and Apache Storm will be integrated. You plan to use four event processing servers that each run as a Kafka consumer. Each server will have a two quad-core processor. You need to identify the minimum number of partitions required to ensure that the load is distributed evenly. How many should you identify?

• A. 1
• B. 4
• C. 16
• D. 32

Answer: B