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NEW QUESTION: 1
A company is moving its fraud detection application from on premises to the AWS Cloud and is using Amazon Neptune for data storage. The company has set up a 1 Gbps AWS Direct Connect connection to migrate 25 TB of fraud detection data from the on-premises data center to a Neptune DB instance. The company already has an Amazon S3 bucket and an S3 VPC endpoint, and 80% of the company's network bandwidth is available.
How should the company perform this data load?
A. Use the AWS CLI to transfer the data from on premises to the S3 bucket. Use the Copy command for Neptune to move the data in bulk from the S3 bucket to the Neptune DB instance.
B. Use AWS DataSync to transfer the data from on premises to the S3 bucket. Use the Loader command for Neptune to move the data in bulk from the S3 bucket to the Neptune DB instance.
C. Use an AWS SDK with a multipart upload to transfer the data from on premises to the S3 bucket. Use the Copy command for Neptune to move the data in bulk from the S3 bucket to the Neptune DB instance.
D. Use AWS Database Migration Service (AWS DMS) to transfer the data from on premises to the S3 bucket. Use the Loader command for Neptune to move the data in bulk from the S3 bucket to the Neptune DB instance.
Answer: B
NEW QUESTION: 2
Which permission would need to be removed from the Development Plan XML in order to keep all goals private?
A. "public-access" permission
B. "move" permission
C. "visibility" permission
D. "share" permission
Answer: D
NEW QUESTION: 3
An IS auditor finds that, at certain times of the day, the data warehouse query
performance decreases significantly. Which of the following controls would it be relevant for the IS auditor to review?
A. Commitment and rollback controls
B. Read/write access log controls
C. User spool and database limit controls
D. Permanent table-space allocation
Answer: C
Explanation:
User spool limits restrict the space available for running user queries. This prevents poorly formed queries from consuming excessive system resources and impacting general query performance. Limiting the space available to users in their own databases prevents them from building excessively large tables. This helps to control space utilization which itself acts to help performance by maintaining a buffer between the actual data volume stored and the physical device capacity. Additionally, it prevents users from consuming excessive resources in ad hoc table builds (as opposed to scheduled production loads that often can run overnight and are optimized for performance purposes), in a data warehouse, since you are not running online transactions, commitment and rollback does not have an impact on performance. The other choices are not as likely to be the root cause of this performance issue.
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