OPTIMIZE_FOR_AD_HOC_WORKLOADS = { ON | OFF }
Enables or disables a compiled plan stub to be stored in cache when a batch is compiled for the first time. The default is OFF. Once the database scoped configuration OPTIMIZE_FOR_AD_HOC_WORKLOADS is enabled for a database, a compiled plan stub will be stored in cache when a batch is compiled for the first time. Plan stubs have a smaller memory footprint compared to the size of the full compiled plan.
Incorrect Answers:
A: LEGACY_CARDINALITY_ESTIMATION = { ON | OFF | PRIMARY }
Enables you to set the query optimizer cardinality estimation model to the SQL Server 2012 and earlier version independent of the compatibility level of the database. The default is OFF, which sets the query optimizer cardinality estimation model based on the compatibility level of the database.
B: QUERY_OPTIMIZER_HOTFIXES = { ON | OFF | PRIMARY }
Enables or disables query optimization hotfixes regardless of the compatibility level of the database. The default is OFF, which disables query optimization hotfixes that were released after the highest available compatibility level was introduced for a specific version (post-RTM).
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/alter-database-scoped-configuration-transact-sql

Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/virtual-machines/windows/sql-server-on-azure-vm-iaas-what-is-overview
https://docs.microsoft.com/en-us/dotnet/architecture/cloud-native/infrastructure-resiliency-azure

Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/execute-as-transact-sql?view=sql-server-ver15
https://docs.microsoft.com/en-us/sql/t-sql/functions/suser-sname-transact-sql?view=sql-server-ver15

Reference:
https://docs.microsoft.com/en-US/troubleshoot/sql/performance/recommendations-reduce-allocation-contention

Explanation:
Scenario: Authenticate database users by using Active Directory credentials.
The configuration steps include the following procedures to configure and use Azure Active Directory authentication.
* Create and populate Azure AD.
* Optional: Associate or change the active directory that is currently associated with your Azure Subscription.
* Create an Azure Active Directory administrator. (Step 1)
* Configure your client computers.
* Create contained database users in your database mapped to Azure AD identities. (Step 2)
* Connect to your database by using Azure AD identities. (Step 3)
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/authentication-aad-overview

Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/virtual-machines/windows/storage-configuration?tabs=windows2016

Section: [none]
Explanation:
Box 1: DTU
Scenario:
* The 30 new databases must scale automatically.
* Once all requirements are met, minimize costs whenever possible.
You can configure resources for the pool based either on the DTU-based purchasing model or the vCore-based purchasing model.
In short, for simplicity, the DTU model has an advantage. Plus, if you’re just getting started with Azure SQL Database, the DTU model offers more options at the lower end of performance, so you can get started at a lower price point than with vCore.
Box 2: An Azure SQL database elastic pool
Azure SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands. The databases in an elastic pool are on a single server and share a set number of resources at a set price. Elastic pools in Azure SQL Database enable SaaS developers to optimize the price performance for a group of databases within a prescribed budget while delivering performance elasticity for each database.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/elastic-pool-overview
https://docs.microsoft.com/en-us/azure/azure-sql/database/reserved-capacity-overview Testlet 2 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
Contoso, Ltd. is a clothing retailer based in Seattle. The company has 2,000 retail stores across the United States and an emerging online presence.
The network contains an Active Directory forest named contoso.com. The forest is integrated with an Azure Active Directory (Azure AD) tenant named contoso.com. Contoso has an Azure subscription associated to the contoso.com Azure AD tenant.
Existing Environment
Transactional Data
Contoso has three years of customer, transaction, operational, sourcing, and supplier data comprised of 10 billion records stored across multiple on-premises Microsoft SQL Server servers. The SQL Server instances contain data from various operations systems. The data is loaded into the instances by using SQL Server Integration Services (SSIS) packages.
You estimate that combining all product sales transactions into a company-wide sales transactions dataset will result in a single table that contains 5 billion rows, with one row per transaction.
Most queries targeting the sales transactions data will be used to identify which products were sold in retail stores and which products were sold online during different time periods. Sales transaction data that is older than three years will be removed monthly.
You plan to create a retail store table that will contain the address of each retail store. The table will be approximately 2 MB. Queries for retail store sales will include the retail store addresses.
You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific product. The product will be identified by a product ID. The table will be approximately 5 GB.
Streaming Twitter Data
The ecommerce department at Contoso develops an Azure logic app that captures trending Twitter feeds referencing the company’s products and pushes the products to Azure Event Hubs.
Planned Changes and Requirements
Planned Changes
Contoso plans to implement the following changes:
* Load the sales transaction dataset to Azure Synapse Analytics.
* Integrate on-premises data stores with Azure Synapse Analytics by using SSIS packages.
* Use Azure Synapse Analytics to analyze Twitter feeds to assess customer sentiments about products.
Sales Transaction Dataset Requirements
Contoso identifies the following requirements for the sales transaction dataset:
* Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong to the partition on the right.
* Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.
* Implement a surrogate key to account for changes to the retail store addresses.
* Ensure that data storage costs and performance are predictable.
* Minimize how long it takes to remove old records.
Customer Sentiment Analytics Requirements
Contoso identifies the following requirements for customer sentiment analytics:
* Allow Contoso users to use PolyBase in an Azure Synapse Analytics dedicated SQL pool to query the content of the data records that host the Twitter feeds. Data must be protected by using row-level security (RLS). The users must be authenticated by using their own Azure AD credentials.
* Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units.
* Store Twitter feeds in Azure Storage by using Event Hubs Capture. The feeds will be converted into Parquet files.
* Ensure that the data store supports Azure AD-based access control down to the object level.
* Minimize administrative effort to maintain the Twitter feed data records.
* Purge Twitter feed data records that are older than two years.
Data Integration Requirements
Contoso identifies the following requirements for data integration:
* Use an Azure service that leverages the existing SSIS packages to ingest on-premises data into datasets stored in a dedicated SQL pool of Azure Synapse Analytics and transform the data.
* Identify a process to ensure that changes to the ingestion and transformation activities can be version- controlled and developed independently by multiple data engineers.

Reference:
https://technet.microsoft.com/windows-server-docs/failover-clustering/deploy-cloud-witness
https://azure.microsoft.com/en-us/support/legal/sla/load-balancer/v1_0/

Reference:
https://docs.microsoft.com/en-us/sql/t-sql/database-console-commands/dbcc-checkdb-transact-sql

1 – Create a database master key.
2 – Create a certificate.
3 – Create a symmetric key.
4 – Open the symmetric key.
Reference:
https://www.sqlshack.com/an-overview-of-the-column-level-sql-server-encryption/

Reference:
https://www.sqlshack.com/automate-azure-sql-database-indexes-and-statistics-maintenance/

In SQL Server, you can also minimize locking contention while protecting transactions from dirty reads of uncommitted data modifications using either:
* The READ COMMITTED isolation level with the READ_COMMITTED_SNAPSHOT database option set to ON.
* The SNAPSHOT isolation level.
If READ_COMMITTED_SNAPSHOT is set to ON (the default on SQL Azure Database), the Database Engine uses row versioning to present each statement with a transactionally consistent snapshot of the data as it existed at the start of the statement. Locks are not used to protect the data from updates by other transactions.
Incorrect Answers:
A: When the PARAMETERIZATION database option is set to SIMPLE, the SQL Server query optimizer may choose to parameterize the queries. This means that any literal values that are contained in a query are substituted with parameters. This process is referred to as simple parameterization. When SIMPLE parameterization is in effect, you cannot control which queries are parameterized and which queries are not.
B: You can specify that all queries in a database be parameterized by setting the PARAMETERIZATION database option to FORCED. This process is referred to as forced parameterization.
C: Delayed transaction durability is accomplished using asynchronous log writes to disk. Transaction log records are kept in a buffer and written to disk when the buffer fills or a buffer flushing event takes place.
Delayed transaction durability reduces both latency and contention within the system.
Some of the cases in which you could benefit from using delayed transaction durability are:
* You can tolerate some data loss.
* You are experiencing a bottleneck on transaction log writes.
* Your workloads have a high contention rate.
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/set-transaction-isolation-level-transact-sql

Example:
Free space for the file in the below query result set will be returned by the FreeSpaceMB column.
SELECT DB_NAME() AS DbName,
name AS FileName,
type_desc,
size/128.0 AS CurrentSizeMB,
size/128.0 – CAST(FILEPROPERTY(name, ‘SpaceUsed’) AS INT)/128.0 AS FreeSpaceMB FROM sys.database_files WHERE type IN (0,1); Reference:
https://www.sqlshack.com/how-to-determine-free-space-and-file-size-for-sql-server-databases/

Premium and Business Critical service tiers leverage the Premium availability model, which integrates compute resources (sqlservr.exe process) and storage (locally attached SSD) on a single node. High availability is achieved by replicating both compute and storage to additional nodes creating a three to four-node cluster.
By default, the cluster of nodes for the premium availability model is created in the same datacenter. With the introduction of Azure Availability Zones, SQL Database can place different replicas of the Business Critical database to different availability zones in the same region. To eliminate a single point of failure, the control ring is also duplicated across multiple zones as three gateway rings (GW).
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/high-availability-sla

Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/serverless-tier-overview

CE: Estimate the vCores needed for the pool as follows:
For vCore-based purchasing model: MAX(<Total number of DBs X average vCore utilization per DB>,<Number of concurrently peaking DBs X Peak vCore utilization per DB)
A: Estimate the storage space needed for the pool by adding the number of bytes needed for all the databases in the pool.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/elastic-pool-overview