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NEW QUESTION: 1
Which three trading partner types are valid for creating trading partner item relationships in Oracle Product Hub Cloud?
A. GS1
B. Competitor
C. Manufacturer
D. Customer
E. Supplier Site
Answer: B,C,D
Explanation:
Explanation/Reference:
Reference: https://docs.oracle.com/en/cloud/saas/supply-chain-management/r13-update17d/fapim/ manage-product-and-service-data-manage-product-relationships-and-associations.html#FAPIM175931

NEW QUESTION: 2
If you change the native VLAN on the trunk port to an unused VLAN, what happens if an attacker attempts a double-tagging attack?
A. A VLAN hopping attack would be prevented.
B. The trunk port would go into an error-disabled state.
C. The attacked VLAN will be pruned.
D. A VLAN hopping attack would be successful.
Answer: A
Explanation:
Explanation
VLAN hopping is a computer security exploit, a method of attacking networked resources on a virtual LAN (VLAN). The basic concept behind all VLAN hopping attacks is for an attacking host on a VLAN to gain access to traffic on other VLANs that would normally not be accessible. There are two primary methods of VLAN hopping: switch spoofing and double tagging.
Double Tagging can only be exploited when switches use "Native VLANs". Double Tagging can be mitigated by either one of the following actions:
+ Simply do not put any hosts on VLAN 1 (The default VLAN)
+ Change the native VLAN on all trunk ports to an unused VLAN ID Source:
https://en.wikipedia.org/wiki/VLAN_hopping

NEW QUESTION: 3
What are two of the benefits of using denormalized data structures in BigQuery?
A. Reduces the amount of data processed, increases query speed
B. Reduces the amount of storage required, increases query speed
C. Reduces the amount of data processed, reduces the amount of storage required
D. Increases query speed, makes queries simpler
Answer: D
Explanation:
Denormalization increases query speed for tables with billions of rows because BigQuery's performance degrades when doing JOINs on large tables, but with a denormalized data structure, you don't have to use JOINs, since all of the data has been combined into one table. Denormalization also makes queries simpler because you do not have to use JOIN clauses. Denormalization increases the amount of data processed and the amount of storage required because it creates redundant data.
Reference:
https://cloud.google.com/solutions/bigquery-data-warehouse#denormalizing_data

NEW QUESTION: 4
Note: This question is part of a series of questions that present the same scenario. Each question on 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.
You are migrating an on-premises application to Azure. One component of the application is a legacy Windows native executable that performs image processing.
The image processing application must run every hour. During times that the image processing application is not running, it should not be consuming any Azure compute resources.
You need to ensure that the image processing application runs correctly every hour.
Solution: Create an Azure Function to run the image processing application every hour.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Explanation/Reference:
Explanation:
It is better to run the legacy application in a VM.

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