HOTSPOT
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.
The health tracking application uses the features of a live dashboard to provide historical and trending.You need to recommend which processing model must be used to process the following types of data:
The top three activities per user on rainy days
The top three activities per user during the last 24 hours
The top activities per geographic region during last 24 hours
The most common sequences of three activities in a row for all of the users
Which processing model should you recommend for each date type? To answer, select the appropriate options
in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

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 extend the dashboard of the health tracking application to summarize fields across several users.
You need to recommend a file format for the activity data in Azure that meets 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.

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. Eachactivity 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.
Users report that when they access data that is more than one year old from a dashboard, the response time is
slow.
You need to resolve the issue that causes the slow response when visualizing older data.
What should you do?

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 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.

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?

DRAG DROP
Your company has a data visualization solution that contains a customized Microsoft Azure Stream Analytics
Solution. The solution provides data to a Microsoft Powel BI deployment.
Every 10 seconds, you need to query for instances that have more than three records.
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 toview content.
NOTE: Each correct selection is worth one point.
Select and Place:

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.

HOTSPOT
You have a Microsoft Azure SQL data warehouse named DW1.
A department in your company creates an Azure SQL database named DB1. DB1 is a data mart.
Each night, you need to insert new rows into 9.000 tables in DB1 from changed data in DW1. The solution must
minimize costs.
What should you use to move the data from DW1 to DB1, and then to import the changed data to DB1? To
answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

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 presentspart of the solution.
NOTE: Each correct selection is worth one point.

Your company has two Microsoft Azure SQL databases named db1 and db2.
You need to move data from a table in db1 to a table in db2 by using a pipeline in Azure Data Factory.
You create an Azure Data Factory named ADF1.
Which two types of objects should you create in ADF1 to complete the pipeline? Each correct answer presents
part of the solution.
NOTE: Each correct selection is worth one point.