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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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A company needs to implement a near-real-time messaging system for hotel inventory. The messages are collected from 1,000 data sources and contain hotel inventory data. The data is then processed and distributed to 20 HTTP endpoint destinations. The range of data size for messages is 2-500 KB. The messages must be delivered to each destination in order. The performance of a single destination HTTP endpointshould not impact the performance of the delivery for other destinations. Which solution meets these requirements with the LOWEST latency from message ingestion to delivery?

Question 103 - DAS-C01 discussion

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A company wants to run analytics on its Elastic Load Balancing logs stored in Amazon S3. A data analyst needs to be able to query all data from a desired year, month, or day. The data analyst should also be able to query a subset of the columns.

The company requires minimal operational overhead and the most cost-effective solution. Which approach meets these requirements for optimizing and querying the log data?

A.
Use an AWS Glue job nightly to transform new log files into .csv format and partition by year, month, and day. Use AWS Glue crawlers to detect new partitions. Use Amazon Athena to query data.
Answers
A.
Use an AWS Glue job nightly to transform new log files into .csv format and partition by year, month, and day. Use AWS Glue crawlers to detect new partitions. Use Amazon Athena to query data.
B.
Launch a long-running Amazon EMR cluster that continuously transforms new log files from Amazon S3 into its Hadoop Distributed File System (HDFS) storage and partitions by year, month, and day. Use Apache Presto to query theoptimized format.
Answers
B.
Launch a long-running Amazon EMR cluster that continuously transforms new log files from Amazon S3 into its Hadoop Distributed File System (HDFS) storage and partitions by year, month, and day. Use Apache Presto to query theoptimized format.
C.
Launch a transient Amazon EMR cluster nightly to transform new log files into Apache ORC format and partition by year, month, and day. Use Amazon Redshift Spectrum to query the data.
Answers
C.
Launch a transient Amazon EMR cluster nightly to transform new log files into Apache ORC format and partition by year, month, and day. Use Amazon Redshift Spectrum to query the data.
D.
Use an AWS Glue job nightly to transform new log files into Apache Parquet format and partition by year, month, and day.Use AWS Glue crawlers to detect new partitions. Use Amazon Athena to query data.
Answers
D.
Use an AWS Glue job nightly to transform new log files into Apache Parquet format and partition by year, month, and day.Use AWS Glue crawlers to detect new partitions. Use Amazon Athena to query data.
Suggested answer: C
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asked 16/09/2024
Jesserey Joseph
44 questions
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