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NEW QUESTION: 1
In 1949, a study of heart disease included 5,137 adults: 2,292 men and 2,845 women. All the individuals were 49 to 70 years of age, and none showed any signs of coronary artery disease. After 14-16 years of careful follow-up, it was found that:
I. 151 men and 37 women showed evidence of coronary artery disease that would account for a heart attack.
II. 102 men and 18 women died of coronary artery disease before they reached the age of 65.
III. 58 percent of the men and 39 percent of the women died within one hour of having a heart attack.
IV. For both men and women, sudden death was more likely if they were under age 55 at the time of the attack.
V. Not all heart attacks produce symptoms. A considerable number of men and women had a myocardial infarction (heart muscle damage) without knowing it. Of those who suffered such "silent coronaries"; 22 percent of the men and 35 percent of the women did not know muscle damage had occurred.
A woman who is 53 years old has a heart attack. Compared with a man, she is more likely to
A. die as the result of a heart attack after age 65
B. have a "silent coronary"
C. die within an hour of the attack
D. die of coronary artery disease before age 65
Answer: B
Explanation:
Explanation/Reference:
Explanation:
NEW QUESTION: 2
Cloud Bigtable is a recommended option for storing very large amounts of
____________________________?
A. single-keyed data with very low latency
B. single-keyed data with very high latency
C. multi-keyed data with very high latency
D. multi-keyed data with very low latency
Answer: A
Explanation:
Explanation
Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, allowing you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key. Cloud Bigtable is ideal for storing very large amounts of single-keyed data with very low latency. It supports high read and write throughput at low latency, and it is an ideal data source for MapReduce operations.
Reference: https://cloud.google.com/bigtable/docs/overview
NEW QUESTION: 3
A company is operating a large customer service call center, and stores and processes call recordings with a custom application Approximately 2% of the call recording are transcribed by an offshore team for quality assurance purposes. These recordings take days. The company uses Linux servers for processing the call recording and managing the transcription queue. There is also a web application for the quality assurance staff to review and score call recordings.
The company plans to migrate the system to AWS to reduce storage costs and the time required to transcribe calls.
Which set of actions should be taken to meet the company's objectives?
A. Use Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer to host the review and scoring application. Upload the call recordings to this application from the call center and store them on an Amazon EFS mount point. Use AWS Backup to archive the call recording after 90 days. Transcribe the call recordings with Amazon Transcribe.
B. Upload the call recording to Amazon S3 from the call center and put the object key in an Amazon SQS queue. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days.
Use Amazon EC2 instances in the queue as the scaling metric. Use Amazon S3, Amazon API Gateway, and AWS Lambda to host the review and scoring application.
C. Upload the call recordings to Amazon S3 from the call center. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use an AWS Lambda trigger to transcribe the call recordings with Amazon Mechanical trunk. Use Amazon EC2 instances in an Auto Scaling group behind an Application Balancer to host the review and scoring application.
D. Upload the call recording to Amazon S3 from the call center. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use an AWS Lambda trigger to transcribe the call recordings with Amazon Transcribe. Use Amazon S3, Amazon API Gateway and Lambda to host the review and scoring application.
Answer: C
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