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NEW QUESTION: 1
A user is buying a laptop. The user will have a lot of personal and confidential information on the laptop.
The user wants to ensure data cannot be accessed by anyone, even if the laptop is stolen. Which of the following should be set up to accomplish this?
A. Compression
B. Auditing
C. Permissions
D. Encryption
Answer: D
NEW QUESTION: 2
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
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.
A database has two tables as shown in the following database diagram:
You need to list all provinces that have at least two large cities. A large city is defined as having a population of at least one million residents. The query must return the following columns:
Solution: You run the following Transact-SQL statement:
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation
The SQL CROSS JOIN produces a result set which is the number of rows in the first table multiplied by the number of rows in the second table if no WHERE clause is used along with CROSS JOIN.This kind of result is called as Cartesian Product.
This is not what is required in this scenario.
References: https://technet.microsoft.com/en-us/library/ms190690(v=sql.105).aspx
NEW QUESTION: 3
What is the semantic difference between the two figures in the exhibit?
A. One is a white-box view, while the other is a black-box view.
B. There is no semantic difference.
C. One is a UML 2.0 diagram, while other is a UML 1.5 diagram.
D. One is a deployment diagram, while the other is a class diagram.
Answer: B
NEW QUESTION: 4
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features