Microsoft 070-775 Actual Free Exam Questions & Community Discussion

You have an Apache Spark cluster in Azure HDInsight.
You execute the following command.

What is the result of running the command?

Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training dat
a. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure HDInsight cluster types for the various tasks associated to the processing pipeline.
You are planning a storage strategy for a large amount of analytic data used for the crime data analytics system. The initial data load involves over 100 billion records, and more than two billion records will be added daily.
You already created an Apache Hadoop cluster in HDInsight premium.
You need to implement the storage strategy to meet the following requirements:
The storage capacity must support 50 TB.
The storage must be optimized for Hadoop.
The data must be stored in its native format.
Enterprise-level security based on Active Directory must be supported.
What should you create?

HOTSPOT
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training dat
a. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure HDInsight cluster types for the various tasks associated to the processing pipeline.
You are using Microsoft Power BI Desktop to create visualizations of the crime data predictions. You connect to a JSON file that is stored in Azure Blob storage.
After loading the data into Power BI, the query shows the following metadata fields only:
Name
Content
Extension
Date created
Date accessed
Date modified
The actual columns have the following names:
Duration
Zip Code
Start Time
Probability
Crime Type
Likelihood Percent
You need to transform the query so that Power BI can access the actual columns rather than the metadata.
Which two actions should you perform from the Edit Queries menu on the Home ribbon? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are building a security tracking solution in Apache Kafka to parse security logs. The security logs record an entry each time a user attempts to access an application. Each log entry contains the IP address used to make the attempt and the country from which the attempt originated.
You need to receive notifications when an IP address from outside of the United States is used to access the application.
Solution: Create new topics. Create a file import process to send messages. Start the consumer and run the producer.
Does this meet the goal?

Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You are planning a big data infrastructure by using an Apache Spark cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The architecture of the infrastructure is shown in the exhibit. (Click the Exhibit button.)

The architecture will be used by the following users:
Support analysts who run applications that will use REST to submit Spark jobs.
Business analysts who use JDBC and ODBC client applications from a real-time view. The business analysts run monitoring queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries.
Data analysts who publish notebooks drawn from batch layer, serving layer, and speed layer queries. All of the notebooks must support native interpreters for data sources that are batch processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The following data sources are used:
Hive for sales data
Apache HBase for operations data
HBase for logistics data by using a single region server
You plan to create a new HBase table to collect the operations dat
a. The workload will be distributed across regional servers. Apache Phoenix will be used on top of HBase for the operations data.
You need to ensure that write operations are distributed across the regional servers.
Which setting should you configure when you create the table?

DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You are planning a big data infrastructure by using an Apache Spark cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The architecture of the infrastructure is shown in the exhibit. (Click the Exhibit button.)

The architecture will be used by the following users:
Support analysts who run applications that will use REST to submit Spark jobs.
Business analysts who use JDBC and ODBC client applications from a real-time view. The business analysts run monitoring queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries.
Data analysts who publish notebooks drawn from batch layer, serving layer, and speed layer queries. All of the notebooks must support native interpreters for data sources that are batch processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The following data sources are used:
Hive for sales data
Apache HBase for operations data
HBase for logistics data by using a single region server
The business analysts require queries to monitor the sales dat
a. The queries must be faster and more interactive than the batch layer queries.
You need to create a new infrastructure to support the queries. The solution must ensure that you can tune the cache policies of the queries.
Which three 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.

You plan to copy data from Azure Blob storage to an Azure SQL database by using Azure Data Factory.
Which file formats can you use?