AWS Certified Data Engineer Associate DEA-C01 Practice Question
A company has 5 TB of structured sales data that analysts query using complex joins, window functions, and aggregations. The queries must return results within seconds during business hours, and the team wants automatic columnar storage compression without managing infrastructure. Which AWS storage platform should be used to host the dataset to meet these performance characteristics?
An AWS Lake Formation data lake on Amazon S3 queried with Amazon Athena
Amazon Redshift is a fully managed, petabyte-scale data warehouse designed for analytic workloads. It stores data in columnar format, applies automatic compression, and distributes processing across nodes, allowing complex SQL queries with joins and aggregations to return in seconds. Amazon RDS is optimized for transactional workloads and can struggle with multi-terabyte analytics at this latency. DynamoDB is a NoSQL key-value store that does not support relational joins. An S3-based data lake managed through AWS Lake Formation provides durable storage but relies on external engines (for example, Amazon Athena) whose performance is typically slower for highly concurrent, complex relational queries compared with a dedicated data warehouse.
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AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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