AWS Certified Data Engineer Associate · Free Practice Question Hard
Question 28
A leading retail analytics company requires processing customer transaction datasets generated during holiday seasons, where data volume can peak unpredictably. The Lead Data Architect needs to select an AWS service that offers both elastic scaling for batch jobs and sophisticated analysis tools capable of deriving insights from petabytes of structured and unstructured data. Which AWS service should the architect choose to cater to high throughput demands while managing costs?
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A
AWS Batch with spot instance orchestration
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B
Amazon EC2 Auto Scaling with optimized compute instances
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C
Amazon Redshift with concurrency scaling
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D
Amazon EMR with transient clusters
Reveal correct answer
Correct answer: D
Explanation
Amazon EMR is well-suited for big data processing and analysis. It supports transient clusters which can be brought up only when needed (such as peak times) and terminated after use, which is cost-effective. It can scale out to handle high workloads, which is ideal for holiday season traffic.
A. AWS Batch with spot instance orchestration is a service that allows you to run batch computing workloads on AWS. While it offers elastic scaling for batch jobs, it may not provide the sophisticated analysis tools required for deriving insights from petabytes of data. Additionally, spot instances can be interrupted, which may not be suitable for critical analytics workloads.
B. Amazon EC2 Auto Scaling with optimized compute instances allows you to automatically adjust the number of EC2 instances based on demand. While it offers elastic scaling, it may not provide the sophisticated analysis tools required for deriving insights from petabytes of data. Additionally, managing costs and optimizing performance may be more challenging compared to using a service like Amazon EMR for this specific use case.
C. Amazon Redshift is a data warehousing service that offers concurrency scaling to handle high throughput demands. While it can manage structured data efficiently, it may not be the best choice for processing unstructured data or running sophisticated analysis tools on petabytes of data.
D. Amazon EMR (Elastic MapReduce) with transient clusters is the correct choice for this scenario. EMR provides elastic scaling for batch jobs and offers sophisticated analysis tools like Apache Spark and Hadoop for processing both structured and unstructured data. Transient clusters help manage costs by spinning up clusters only when needed, making it ideal for processing peak holiday season datasets.
Discussion
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