최신 070-475日本語 무료덤프 - Microsoft Design and Implement Big Data Analytics Solutions (070-475日本語版)

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Explanation

Group A: Tumbling
Tumbling Windows define a repeating, non-overlapping window of time.
Group B: Hopping
Like Tumbling Windows, Hopping Windows move forward in time by a fixed period but they can overlap with one another.

Explanation

Box 1: Azure Data Factory
Use the Copy Activity in Azure Data Factory to move data to/from Azure SQL Data Warehouse.
Box 2: The BULK INSERT statement

Explanation

Step 1: Configure a Microsoft Data Management Gateway
Install and configure Azure Data Factory Integration Runtime.
The Integration Runtime is a customer managed data integration infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments. This runtime was formerly called
"Data Management Gateway".
Step 2: Create a linked service for Azure Blob storage
Create an Azure Storage linked service (destination/sink). You link your Azure storage account to the data factory.
Step 3: Create a linked service for SQL Server
Create and encrypt a SQL Server linked service (source)
In this step, you link your on-premises SQL Server instance to the data factory.
Step 4: Create an input dataset and an output dataset.
Create a dataset for the source SQL Server database. In this step, you create input and output datasets. They represent input and output data for the copy operation, which copies data from the on-premises SQL Server database to Azure Blob storage.
Step 5: Create a pipeline..
You create a pipeline with a copy activity. The copy activity uses SqlServerDataset as the input dataset and AzureBlobDataset as the output dataset. The source type is set to SqlSource and the sink type is set to BlobSink.
References: https://docs.microsoft.com/en-us/azure/data-factory/tutorial-hybrid-copy-powershell

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Explanation

Box 1: Security
Security Policy
Example: After we have created Predicate function, we have to bind it to the table, using Security Policy. We will be using CREATE SECURITY POLICY command to set the security policy in place.
CREATE SECURITY POLICY DepartmentSecurityPolicy
ADD FILTER PREDICATE dbo.DepartmentPredicateFunction(UserDepartment) ON dbo.Department WITH(STATE = ON) Box 2: Filter
[ FILTER | BLOCK ]
The type of security predicate for the function being bound to the target table. FILTER predicates silently filter the rows that are available to read operations. BLOCK predicates explicitly block write operations that violate the predicate function.
Box 3: Block
Box 4: Block
Box 5: Filter
Topic 2, Litware, Inc
Overview
General 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 horn a user's personal device to Microsoft Azure.
Physical Locations
Litware has three development and commercial offices. The offices are located in the Untied States, Luxembourg, and India.
Litware products are sold worldwide. Litware has commercial representatives in more than 80 countries.
Existing Environment
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 Health Tracking Application
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.
Machine Learning Experiments
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
Planned Changes
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.
Business Goals
Minimize the costs associated with transferring data from the event hub to Azure Storage.
Technical Requirements
Litware identities the following technical requirements:
Data from the devices must be stored from three years in a format that enables the fast processing of data 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.
Privacy Requirements
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.
Other Technical Requirements
When the Litware health tracking application asks users how they feel, their responses must be reported to Azure.

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