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A company wants to research user turnover by analyzing the past 3 months of user activities. With millions of users, 1.5 TB of uncompressed data is generated each day. A 30-node Amazon Redshift cluster with 2.56 TB of solid state drive (SSD) storage for each node is required to meet the query performance goals. The company wants to run an additional analysis on a year’s worth of historical data to examine trends indicating which features are most popular. This analysis will be done once a week. What is the MOST cost-effective solution?
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A company wants to optimize the cost of its data and analytics platform. The company is ingesting a number of .csv and JSON files in Amazon S3 from various data sources. Incoming data is expected to be 50 GB each day. The company is using Amazon Athena to query the raw data in Amazon S3 directly. Most queries aggregate data from the past 12 months, and data that is older than 5 years is infrequently queried. The typical query scans about 500 MB of data and is expected to return results in less than 1 minute. The raw data must be retained indefinitely for compliance requirements. Which solution meets the company’s requirements?
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Question 51 - DAS-C01 discussion

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A reseller that has thousands of AWS accounts receives AWS Cost and Usage Reports in an Amazon S3 bucket. The reports are delivered to the S3 bucket in the following format:

//yyyymmdd-yyyymmdd/.parquet

An AWS Glue crawler crawls the S3 bucket and populates an AWS Glue Data Catalog with a table. Business analysts use Amazon Athena to query the table and create monthly summary reports for the AWS accounts. The business analysts are experiencing slow queries because of the accumulation of reports from the last 5 years. The business analysts want the operations team to make changes to improve query performance. Which action should the operations team take to meet these requirements?

A.
Change the file format to .csv.zip
Answers
A.
Change the file format to .csv.zip
B.
Partition the data by date and account ID
Answers
B.
Partition the data by date and account ID
C.
Partition the data by month and account ID
Answers
C.
Partition the data by month and account ID
D.
Partition the data by account ID, year, and month
Answers
D.
Partition the data by account ID, year, and month
Suggested answer: A

Explanation:


Reference: https://docs.aws.amazon.com/cur/latest/userguide/access-cur-s3.html

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asked 16/09/2024
Maxwell Konetzki
29 questions
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