




Explanation

Azure Data Factory can be used to orchestrate the execution of stored procedures. This allows more complex pipelines to be created and extends Azure Data Factory's ability to leverage the computational power of SQL Data Warehouse.
From scenario:
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 identifies the following requirements for DB1:
* Data generated by the streaming analytics platform must be stored in DB1.
* The advertisers in DB1 must be stored in a table named Table1 and must be refreshed nightly.




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.




Explanation

From Scenario: Relecloud plans to implement a data warehouse named DB2.
Box 1: Temporal table
From Scenario:
Relecloud identifies the following requirements for DB2:
Users must be able to view previous versions of the data in DB2 by using aggregates.
DB2 must be able to store more than 40 TB of data.
A system-versioned temporal table is a new type of user table in SQL Server 2017, designed to keep a full history of data changes and allow easy point in time analysis. A temporal table also contains a reference to another table with a mirrored schema. The system uses this table to automatically store the previous version of the row each time a row in the temporal table gets updated or deleted. This additional table is referred to as the history table, while the main table that stores current (actual) row versions is referred to as the current table or simply as the temporal table.






