You are designing an Azure Synapse Analytics dedicated SQL pool.
Groups will have access to sensitive data in the pool as shown in the following table.

You have policies for the sensitive dat
a. The policies vary be region as shown in the following table.

You have a table of patients for each region. The tables contain the following potentially sensitive columns.

You are designing dynamic data masking to maintain compliance.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Correct Answer:

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

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You are building a database in an Azure Synapse Analytics serverless SQL pool.
You have data stored in Parquet files in an Azure Data Lake Storege Gen2 container.
Records are structured as shown in the following sample.
{
"id": 123,
"address_housenumber": "19c",
"address_line": "Memory Lane",
"applicant1_name": "Jane",
"applicant2_name": "Dev"
}
The records contain two applicants at most.
You need to build a table that includes only the address fields.
How should you complete the Transact-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables

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You have two fact tables named Flight and Weather. Queries targeting the tables will be based on the join between the following columns.

You need to recommend a solution that maximizes query performance.
What should you include in the recommendation?

• A.In the tables use a hash distribution of ArrivalDateTime and ReportDateTime.
• B.In the tables use a hash distribution of ArrivaIAirportID and AirportlD.
• C.In each table, create an identity column.
• D.In each table, create a column as a composite of the other two columns in the table.

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You need to schedule an Azure Data Factory pipeline to execute when a new file arrives in an Azure Data Lake Storage Gen2 container.
Which type of trigger should you use?

• A.on-demand
• B.tumbling window
• C.schedule
• D.storage event

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You are designing an inventory updates table in an Azure Synapse Analytics dedicated SQL pool. The table will have a clustered columnstore index and will include the following columns:
* EventDate: 1 million per day
* EventTypelD: 10 million per event type
* WarehouselD: 100 million per warehouse
* ProductCategoryTypeiD: 25 million per product category type
You identify the following usage patterns:
Analyst will most commonly analyze transactions for a warehouse.
Queries will summarize by product category type, date, and/or inventory event type.
You need to recommend a partition strategy for the table to minimize query times.
On which column should you recommend partitioning the table?

• A.WarehouseID
• B.ProductCategoryTypeID
• C.EventDate
• D.EventTypeID

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