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Answer: AWS Glue with data catalog
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to move data between data stores. It can be used to build a data lake on AWS by ingesting, transforming, and loading both structured and unstructured data from various sources into a centralized data store like Amazon S3. To optimize for data ingestion and storage, you can use AWS Glue to create ETL jobs that extract data from the source systems, transform the data into the desired format, and load it into the data lake. You can also use the AWS Glue data catalog to manage the metadata and schema of the data in the data lake.
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Your company is planning to implement a data lake on AWS. The data lake should be able to handle both structured and unstructured data from various sources. Which AWS service should you use, and how should you configure it to optimize for data ingestion and storage?
A
Amazon S3 with server-side encryption
B
Amazon Redshift with columnar storage
C
Amazon DynamoDB with on-demand capacity mode
D
AWS Glue with data catalog
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