You have the resources shown in the following table.CDB1 hosts a container that stores continuously updated operational data.You are designing a solution that will use AS1 to analyze the operational data daily.You need to recommend a solution to analyze the data without affecting the performance of the operational data store.What should you include in the recommendation?
Answer(s): C
Azure Synapse Link for Azure Cosmos DB is a cloud-native hybrid transactional and analytical processing (HTAP) capability that enables near real time analytics over operational data in Azure Cosmos DB. Azure Synapse Link creates a tight seamless integration between Azure Cosmos DB and Azure Synapse Analytics.Azure Cosmos DB analytical store, a fully isolated column store, can be used with Azure Synapse Link to enable Extract-Transform-Load (ETL) analytics in Azure Synapse Analytics against your operational data at scale. Business analysts, data engineers, and data scientists can now use Synapse Spark or Synapse SQL interchangeably to run near real time business intelligence, analytics, and machine learning pipelines. You can analyze real time data without affecting the performance of your transactional workloads on Azure Cosmos DB.The following image shows the Azure Synapse Link integration with Azure Cosmos DB and Azure Synapse Analytics:
https://learn.microsoft.com/en-us/azure/cosmos-db/synapse-link
HOTSPOT (Drag and Drop is not supported)You have an Azure subscription. The subscription contains an Azure SQL managed instance that stores employee details, including social security numbers and phone numbers.You need to configure the managed instance to meet the following requirements:The helpdesk team must see only the last four digits of an employee’s phone number.Cloud administrators must be prevented from seeing the employee’s social security numbers.What should you enable for each column in the managed instance? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Answer(s): A
Box 1: Dynamic data maskingThe helpdesk team must see only the last four digits of an employee’s phone number.Dynamic data masking helps prevent unauthorized access to sensitive data by enabling customers to designate how much of the sensitive data to reveal with minimal effect on the application layer. It’s a policy-based security feature that hides the sensitive data in the result set of a query over designated database fields, while the data in the database isn’t changed.Masking functions: A set of methods that control the exposure of data for different scenarios.* Credit cardMasking method, which exposes the last four digits of the designated fields and adds a constant string as a prefix in the form of a credit card.XXXX-XXXX-XXXX-1234Box 2: Always EncryptedCloud administrators must be prevented from seeing the employee’s social security numbers.Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national/ regional identification numbers (for example, U.S. social security numbers), stored in Azure SQL Database, Azure SQL Managed Instance, and SQL Server databases. Always Encrypted allows clients to encrypt sensitive data inside client applications and never reveal the encryption keys to the Database Engine. This provides a separation between those who own the data and can view it, and those who manage the data but should have no access – on-premises database administrators, cloud database operators, or other high-privileged unauthorized users. As a result, Always Encrypted enables customers to confidently store their sensitive data in the cloud, and to reduce the likelihood of data theft by malicious insiders.
https://learn.microsoft.com/en-us/sql/relational-databases/security/encryption/always-encrypted-database- engine https://learn.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview
You plan to use an Azure Storage account to store data assets.You need to recommend a solution that meets the following requirements:Supports immutable storageDisables anonymous access to the storage accountSupports access control list (ACL)-based Microsoft Entra permissionsWhat should you include in the recommendation?
Answer(s): B
HOTSPOT (Drag and Drop is not supported)You are designing a storage solution that will ingest, store, and analyze petabytes (PBs) of structured, semi- structured, and unstructured text data. The analyzed data will be offloaded to Azure Data Lake Storage Gen2 for long-term retention.You need to recommend a storage and analytics solution that meets the following requirements:Stores the processed dataProvides interactive analyticsSupports manual scaling, built-in autoscaling, and custom autoscalingWhat should you include in the recommendation? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Box 1: Azure Data Lake AnalyticsStores the processed dataProvides interactive analyticsAzure Data Lake Analytics is an on-demand analytics job service that simplifies big data. Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and extract valuable insights. The analytics service can handle jobs of any scale instantly by setting the dial for how much power you need. You only pay for your job when it’s running, making it cost-effective.U-SQL: simple and familiar, powerful, and extensibleData Lake Analytics includes U-SQL, a query language that extends the familiar, simple, declarative nature of SQL with the expressive power of C#. The U-SQL language uses the same distributed runtime that powers Microsoft’s internal exabyte-scale data lake. SQL and .NET developers can now process and analyze their data with the skills they already have.Box 2: U-SQLGet started with U-SQL in Azure Data Lake AnalyticsU-SQL is a language that combines declarative SQL with imperative C# to let you process data at any scale. Through the scalable, distributed-query capability of U-SQL, you can efficiently analyze data across relational stores such as Azure SQL Database. With U-SQL, you can process unstructured data by applying schema on read and inserting custom logic and UDFs. Additionally, U-SQL includes extensibility that gives you fine-grained control over how to execute at scale.
https://learn.microsoft.com/en-us/azure/data-lake-analytics/data-lake-analytics-u-sql-get-started
HOTSPOT (Drag and Drop is not supported)You plan to use Azure SQL as a database platform.You need to recommend an Azure SQL product and service tier that meets the following requirements:Automatically scales compute resources based on the workload demandProvides per second billingWhat should you recommend? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Box 1: A single Azure SQL DatabaseAzure SQL productServerless is a compute tier for single databases in Azure SQL Database that automatically scales compute based on workload demand and bills for the amount of compute used per second.The serverless compute tier for single databases in Azure SQL Database is parameterized by a compute autoscaling range and an auto-pause delay.Box 2: General PurposeService tierThe serverless compute tier is available in the General Purpose service tier and currently in preview in the Hyperscale service tier.
https://learn.microsoft.com/en-us/azure/azure-sql/database/serverless-tier-overview
Post your Comments and Discuss Microsoft AZ-305 exam prep with other Community members:
Our website is free, but we have to fight against AI bots and content theft. We're sorry for the inconvenience caused by these security measures. You can access the rest of the AZ-305 content, but please register or login to continue.