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NEW QUESTION: 1
You plan to create an Azure Synapse Analytics dedicated SQL pool.
You need to minimize the time it takes to identify queries that return confidential information as defined by the company's data privacy regulations and the users who executed the queries.
Which two components should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. dynamic data masking for columns that contain confidential information
B. sensitivity-classification labels applied to columns that contain confidential information
C. resource tags for databases that contain confidential information
D. audit logs sent to a Log Analytics workspace
Answer: A,B
Explanation:
Reference:
https://www.sqlshack.com/understanding-azure-synapse-analytics-formerly-sql-dw/

NEW QUESTION: 2
What type of measure does NOT have Drill to Detail capability?
Please choose the correct answer.
Response:
A. Derived input measure
B. Custom measure
C. Base input measure
D. Result measure
Answer: A

NEW QUESTION: 3
A large company is rolling out Einstein Analytics to their field sales. They have a well-defined role hierarchy where everyone is assigned to an appropriate node on the hierarchy.
An individual Sales rep should be able to view all opportunities that she/he owns or as part of the account team or opportunity team. The Sales Manager should be able to view all opportunities for the entire Sales team.
Similarly, the Sales Vice President should be able to view opportunities for everyone who rolls up in that hierarchy.
The opportunity dataset has a field called 'Ownerld' which represents the opportunity owner.
Given this information, how can an Einstein Consultant implement the above requirements?
A. As part of the dataflow, use the flatten operation on the role hierarchy and create a multivalue attribute called 'ParentRolelDs' on the opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" &&
'Ownerld' == "SUser.Id".
B. As part of the dataflow, use computeRelative on the Roleld field to create an attribute called
'ParentRolelDs' on the opportunity
dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || 'Ownerld' ==
"$User.Id".
C. As part of the dataflow, use computeExpression on the Roleld field to create an attribute called
'ParentRolelDs' on the opportunity
dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || 'Ownerld' ==
"$User.Id".
D. As part of the dataflow, use the flatten operation on the role hierarchy and create a multivalue attribute called 'ParentRolelDs' on the opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || TeamMember.Id' == "$User. Id" || 'Ownerld' == "SUser.Id".
Answer: D

NEW QUESTION: 4
In einem Datenbankverwaltungssystem (DBMS) wird die Normalisierung verwendet, um:
A. Reduzieren Sie die Datenredundanz
B. Standardisieren Sie Datennamen
C. Verarbeitungs-Deadlocks beseitigen
D. Reduzieren Sie die Zugriffszeit
Answer: A