Microsoft Microsoft Certifications DP-203 Questions & Answers

• Question 211:

  You are designing an Azure Synapse solution that will provide a query interface for the data stored in an Azure Storage account. The storage account is only accessible from a virtual network.

  You need to recommend an authentication mechanism to ensure that the solution can access the source data.

  What should you recommend?

  A. a managed identity

  B. anonymous public read access

  C. a shared key

  Correct Answer: A

  Managed Identity authentication is required when your storage account is attached to a VNet.

  Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/quickstart-bulk-load-copy-tsql-examples

• Question 212:

  You are developing an application that uses Azure Data Lake Storage Gen2.

  You need to recommend a solution to grant permissions to a specific application for a limited time period.

  What should you include in the recommendation?

  A. role assignments

  B. shared access signatures (SAS)

  C. Azure Active Directory (Azure AD) identities

  D. account keys

  Correct Answer: B

  A shared access signature (SAS) provides secure delegated access to resources in your storage account. With a SAS, you have granular control over how a client can access your data. For example:

  What resources the client may access.

  What permissions they have to those resources.

  How long the SAS is valid.

  Reference:

  https://docs.microsoft.com/en-us/azure/storage/common/storage-sas-overview

• Question 213:

  You have a SQL pool in Azure Synapse that contains a table named dbo.Customers. The table contains a column name Email.

  You need to prevent nonadministrative users from seeing the full email addresses in the Email column. The users must see values in a format of a [email protected] instead.

  What should you do?

  A. From Microsoft SQL Server Management Studio, set an email mask on the Email column.

  B. From the Azure portal, set a mask on the Email column.

  C. From Microsoft SQL Server Management Studio, grant the SELECT permission to the users for all the columns in the dbo.Customers table except Email.

  D. From the Azure portal, set a sensitivity classification of Confidential for the Email column.

  Correct Answer: A

  From Microsoft SQL Server Management Studio, set an email mask on the Email column. This is because "This feature cannot be set using portal for Azure Synapse (use PowerShell or REST API) or SQL Managed Instance." So use Create table statement with Masking e.g. CREATE TABLE Membership (MemberID int IDENTITY PRIMARY KEY, FirstName varchar(100) MASKED WITH (FUNCTION = 'partial(1,"XXXXXXX",0)') NULL, . . upvoted 24 times

  [email protected]

  Reference: https://docs.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview

• Question 214:

  You have an Azure Data Lake Storage Gen2 account named adls2 that is protected by a virtual network.

  You are designing a SQL pool in Azure Synapse that will use adls2 as a source.

  What should you use to authenticate to adls2?

  A. an Azure Active Directory (Azure AD) user

  B. a shared key

  C. a shared access signature (SAS)

  D. a managed identity

  Correct Answer: D

  Managed identity for Azure resources is a feature of Azure Active Directory. The feature provides Azure services with an automatically managed identity in Azure AD. You can use the Managed Identity capability to authenticate to any service that support Azure AD authentication.

  Managed Identity authentication is required when your storage account is attached to a VNet.

  Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/quickstart-bulk-load-copy-tsql-examples

• Question 215:

  You are designing a security model for an Azure Synapse Analytics dedicated SQL pool that will support multiple companies.

  You need to ensure that users from each company can view only the data of their respective company.

  Which two objects should you include in the solution? Each correct answer presents part of the solution.

  NOTE: Each correct selection is worth one point.

  A. a security policy

  B. a custom role-based access control (RBAC) role

  C. a function

  D. a column encryption key

  E. asymmetric keys

  Correct Answer: AB

  A: Row-Level Security (RLS) enables you to use group membership or execution context to control access to rows in a database table. Implement RLS by using the CREATE SECURITY POLICYTransact-SQL statement.

  B: Azure Synapse provides a comprehensive and fine-grained access control system, that integrates:

  1.

  Azure roles for resource management and access to data in storage,

  2.

  Synapse roles for managing live access to code and execution,

  3.

  SQL roles for data plane access to data in SQL pools.

  Reference: https://docs.microsoft.com/en-us/sql/relational-databases/security/row-level-security https://docs.microsoft.com/en-us/azure/synapse-analytics/security/synapse-workspace-access-control-overview

• Question 216:

  You plan to build a structured streaming solution in Azure Databricks. The solution will count new events in five-minute intervals and report only events that arrive during the interval. The output will be sent to a Delta Lake table.

  Which output mode should you use?

  A. update

  B. complete

  C. append

  Correct Answer: C

  Append Mode: Only new rows appended in the result table since the last trigger are written to external storage. This is applicable only for the queries where existing rows in the Result Table are not expected to change. Incorrect Answers:

  B: Complete Mode: The entire updated result table is written to external storage. It is up to the storage connector to decide how to handle the writing of the entire table.

  A: Update Mode: Only the rows that were updated in the result table since the last trigger are written to external storage. This is different from Complete Mode in that Update Mode outputs only the rows that have changed since the last trigger. If the query doesn't contain aggregations, it is equivalent to Append mode.

  Reference: https://docs.databricks.com/getting-started/spark/streaming.html

• Question 217:

  You are creating a new notebook in Azure Databricks that will support R as the primary language but will also support Scala and SQL. Which switch should you use to switch between languages?

  A. %

  B. @

  C. \\[]

  D. \\()

  Correct Answer: A

  To change the language in Databricks’ cells to either Scala, SQL, Python or R, prefix the cell with ‘%’, followed by the language.

  %python //or r, scala, sql

  Reference:

  https://www.theta.co.nz/news-blogs/tech-blog/enhancing-digital-twins-part-3-predictive-maintenance-with-azure-databricks

• Question 218:

  You have an Azure Data Factory pipeline that performs an incremental load of source data to an Azure Data Lake Storage Gen2 account.

  Data to be loaded is identified by a column named LastUpdatedDate in the source table.

  You plan to execute the pipeline every four hours.

  You need to ensure that the pipeline execution meets the following requirements:

  1.

  Automatically retries the execution when the pipeline run fails due to concurrency or throttling limits.

  2.

  Supports backfilling existing data in the table. Which type of trigger should you use?

  A. event

  B. on-demand

  C. on-demand

  D. tumbling window

  Correct Answer: D

  In case of pipeline failures, tumbling window trigger can retry the execution of the referenced pipeline automatically, using the same input parameters, without the user intervention. This can be specified using the property "retryPolicy" in the trigger definition.

  Reference: https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-tumbling-window-trigger

• Question 219:

  After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

  You have an Azure Data Lake Storage account that contains a staging zone.

  You need to design a daily process to ingest incremental data from the staging zone, transform the data by executing an R script, and then insert the transformed data into a data warehouse in Azure Synapse Analytics.

  Solution: You use an Azure Data Factory schedule trigger to execute a pipeline that copies the data to a staging table in the data warehouse, and then uses a stored procedure to execute the R script.

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: A

  If you need to transform data in a way that is not supported by Data Factory, you can create a custom activity with your own data processing logic and use the activity in the pipeline. Note: You can use data transformation activities in Azure Data Factory and Synapse pipelines to transform and process your raw data into predictions and insights at scale. Reference:

  https://docs.microsoft.com/en-us/azure/data-factory/transform-data

• Question 220:

  You are designing an Azure Databricks cluster that runs user-defined local processes. You need to recommend a cluster configuration that meets the following requirements:

  1.

  Minimize query latency.

  2.

  Maximize the number of users that can run queries on the cluster at the same time.

  3.

  Reduce overall costs without compromising other requirements. Which cluster type should you recommend?

  A. Standard with Auto Termination

  B. High Concurrency with Autoscaling

  C. High Concurrency with Auto Termination

  D. Standard with Autoscaling

  Correct Answer: B

  A High Concurrency cluster is a managed cloud resource. The key benefits of High Concurrency clusters are that they provide fine-grained sharing for maximum resource utilization and minimum query latencies.

  Databricks chooses the appropriate number of workers required to run your job. This is referred to as autoscaling. Autoscaling makes it easier to achieve high cluster utilization, because you don't need to provision the cluster to match a

  workload.

  Incorrect Answers:

  C: The cluster configuration includes an auto terminate setting whose default value depends on cluster mode:

  Standard and Single Node clusters terminate automatically after 120 minutes by default. High Concurrency clusters do not terminate automatically by default.

  Reference: https://docs.microsoft.com/en-us/azure/databricks/clusters/configure