Topic 3, Litware, inc
Overview
General Overview
Litware, Inc, is an international car racing and manufacturing company that has 1,000 employees. Most employees are located in Europe. The company supports racing teams that complete in a worldwide racing series.
Physical Locations
Litware has two main locations: a main office in London, England, and a manufacturing plant in Berlin, Germany.
During each race weekend, 100 engineers set up a remote portable office by using a VPN to connect the datacentre in the London office. The portable office is set up and torn down in approximately 20 different countries each year.
Existing environment
Race Central
During race weekends, Litware uses a primary application named Race Central. Each car has several sensors that send real-time telemetry data to the London datacentre. The data is used for real-time tracking of the cars.
Race Central also sends batch updates to an application named Mechanical Workflow by using Microsoft SQL Server Integration Services (SSIS).
The telemetry data is sent to a MongoDB database. A custom application then moves the data to databases in SQL Server 2017. The telemetry data in MongoDB has more than 500 attributes. The application changes the attribute names when the data is moved to SQL Server 2017.
The database structure contains both OLAP and OLTP databases.
Mechanical Workflow
Mechanical Workflow is used to track changes and improvements made to the cars during their lifetime.
Currently, Mechanical Workflow runs on SQL Server 2017 as an OLAP system.
Mechanical Workflow has a named Table1 that is 1 TB. Large aggregations are performed on a single column of Table 1.
Requirements
Planned Changes
Litware is the process of rearchitecting its data estate to be hosted in Azure. The company plans to decommission the London datacentre and move all its applications to an Azure datacentre.
Technical Requirements
Litware identifies the following technical requirements:
Data collection for Race Central must be moved to Azure Cosmos DB and Azure SQL Database. The data must be written to the Azure datacentre closest to each race and must converge in the least amount of time.
The query performance of Race Central must be stable, and the administrative time it takes to perform optimizations must be minimized.
The datacentre for Mechanical Workflow must be moved to Azure SQL data Warehouse.
Transparent data encryption (IDE) must be enabled on all data stores, whenever possible.
An Azure Data Factory pipeline must be used to move data from Cosmos DB to SQL Database for Race Central. If the data load takes longer than 20 minutes, configuration changes must be made to Data Factory.
The telemetry data must migrate toward a solution that is native to Azure.
The telemetry data must be monitored for performance issues. You must adjust the Cosmos DB Request Units per second (RU/s) to maintain a performance SLA while minimizing the cost of the Ru/s.
Data Masking Requirements
During rare weekends, visitors will be able to enter the remote portable offices. Litware is concerned that some proprietary information might be exposed. The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
Only show the last four digits of the values in a column named SuspensionSprings.
Only Show a zero value for the values in a column named ShockOilWeight.

Explanation
Use the Azure Key Vault, not the Windows Certificate Store, to store the master key.
Note: The Master Key Configuration page is where you set up your CMK (Column Master Key) and select the key store provider where the CMK will be stored. Currently, you can store a CMK in the Windows certificate store, Azure Key Vault, or a hardware security module (HSM).

References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-always-encrypted-azure-key-vault
Topic 2, Proseware Inc
Background
Proseware, Inc, develops and manages a product named Poll Taker. The product is used for delivering public opinion polling and analysis.
Polling data comes from a variety of sources, including online surveys, house-to-house interviews, and booths at public events.
Polling data
Polling data is stored in one of the two locations:
* An on-premises Microsoft SQL Server 2019 database named PollingData
* Azure Data Lake Gen 2
Data in Data Lake is queried by using PolyBase
Poll metadata
Each poll has associated metadata with information about the poll including the date and number of respondents. The data is stored as JSON.
Phone-based polling
Security
* Phone-based poll data must only be uploaded by authorized users from authorized devices
* Contractors must not have access to any polling data other than their own
* Access to polling data must set on a per-active directory user basis
Data migration and loading
* All data migration processes must use Azure Data Factory
* All data migrations must run automatically during non-business hours
* Data migrations must be reliable and retry when needed
Performance
After six months, raw polling data should be moved to a lower-cost storage solution.
Deployments
* All deployments must be performed by using Azure DevOps. Deployments must use templates used in multiple environments
* No credentials or secrets should be used during deployments
Reliability
All services and processes must be resilient to a regional Azure outage.
Monitoring
All Azure services must be monitored by using Azure Monitor. On-premises SQL Server performance must be monitored.

You can use the Delete Activity in Azure Data Factory to delete files or folders from on-premises storage stores or cloud storage stores.
Azure Blob storage is supported.
Note: You can also apply an Azure Blob storage lifecycle policy.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/delete-activity
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-lifecycle-management-concepts?tabs=azure- portal Implement data storage solutions Testlet 2 Case Study This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
General Overview
Litware, Inc. is an international car racing and manufacturing company that has 1,000 employees. Most employees are located in Europe. The company supports racing teams that complete in a worldwide racing series.
Physical Locations
Litware has two main locations: a main office in London, England, and a manufacturing plant in Berlin, Germany.
During each race weekend, 100 engineers set up a remote portable office by using a VPN to connect the datacenter in the London office. The portable office is set up and torn down in approximately 20 different countries each year.
Existing environment
Race Central
During race weekends, Litware uses a primary application named Race Central. Each car has several sensors that send real-time telemetry data to the London datacentre. The data is used for real-time tracking of the cars.
Race Central also sends batch updates to an application named Mechanical Workflow by using Microsoft SQL Server Integration Services (SSIS).
The telemetry data is sent to a MongoDB database. A custom application then moves the data to databases in SQL Server 2017. The telemetry data in MongoDB has more than 500 attributes. The application changes the attribute names when the data is moved to SQL Server 2017.
The database structure contains both OLAP and OLTP databases.
Mechanical Workflow
Mechanical Workflow is used to track changes and improvements made to the cars during their lifetime.
Currently, Mechanical Workflow runs on SQL Server 2017 as an OLAP system.
Mechanical Workflow has a table named Table1 that is 1 TB. Large aggregations are performed on a single column of Table1.
Requirements
Planned Changes
Litware is in the process of rearchitecting its data estate to be hosted in Azure. The company plans to decommission the London datacentre and move all its applications to an Azure datacenter.
Technical Requirements
Litware identifies the following technical requirements:
* Data collection for Race Central must be moved to Azure Cosmos DB and Azure SQL Database. The data must be written to the Azure datacenter closest to each race and must converge in the least amount of time.
* The query performance of Race Central must be stable, and the administrative time it takes to perform optimizations must be minimized.
* The database for Mechanical Workflow must be moved to Azure Synapse Analytics.
* Transparent data encryption (TDE) must be enabled on all data stores, whenever possible.
* An Azure Data Factory pipeline must be used to move data from Cosmos DB to SQL Database for Race Central. If the data load takes longer than 20 minutes, configuration changes must be made to Data Factory.
* The telemetry data must migrate toward a solution that is native to Azure.
* The telemetry data must be monitored for performance issues. You must adjust the Cosmos DB Request Units per second (RU/s) to maintain a performance SLA while minimizing the cost of the RU/s.
Data Masking Requirements
During race weekends, visitors will be able to enter the remote portable offices. Litware is concerned that some proprietary information might be exposed. The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
* Only show the last four digits of the values in a column named SuspensionSprings.
* Only show a zero value for the values in a column named ShockOilWeight.

See the explanation below.
Explanation
Set up auditing for your database
The following section describes the configuration of auditing using the Azure portal.
1. Go to the Azure portal.
2. Navigate to Auditing under the Security heading in your SQL database db2/server pane

3. If you prefer to enable auditing on the database level, switch Auditing to ON.

Note: By default the audit database data retention period is set to 100 days.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-auditing

Explanation
Copying between a cloud data source and a data source in private network: if either source or sink linked service points to a self-hosted IR, the copy activity is executed on that self-hosted Integration Runtime.
References:
https://docs.microsoft.com/en-us/azure/data-factory/concepts-integration-runtime#determining-which-ir-to-use