AWS Certified Data Engineer Associate Certification
Question 1
A company needs to migrate data monthly from an on-premises Microsoft SQL Server database to Amazon RDS for SQL Server but wants to reduce migration costs and minimize downtime. Which AWS service meets these needs?
A. AWS Lambda
B. AWS Database Migration Service (AWS DMS)
C. AWS Direct Connect
D. AWS DataSync
Question 2
A company is building an analytics solution using Amazon S3 for a data lake and Amazon Redshift for a data warehouse. They plan to use Amazon Redshift Spectrum to query data in Amazon S3. Which actions will provide the fastest query performance? (Choose two.)
A. Use gzip compression to compress files between 1 GB and 5 GB.
B. Use a columnar storage file format.
C. Partition data based on common query predicates.
D. Split data into files less than 10 KB.
E. Use file formats that are not splittable.
Question 3
A company stores semi-structured data in an S3 data lake. A data engineer must perform change data capture (CDC) on daily JSON snapshots to identify data changes. Which solution captures the changed data most cost-effectively?
A. Use an AWS Lambda function to compare previous and current data.
B. Ingest data into Amazon RDS for MySQL and use AWS DMS for CDC.
C. Use an open-source data lake format to merge the source data with the data lake in S3.
D. Use Aurora Serverless and AWS DMS for CDC to the data lake.
Question 4
A company needs to persist data generated by an application running on Amazon EC2, even if instances are terminated. A data engineer must configure new EC2 instances to retain the application data. Which solution meets this requirement?
A. Launch instances with an AMI backed by an EC2 instance store volume containing the data.
B. Launch instances with an AMI backed by a root Amazon EBS volume containing the data.
C. Launch instances with an AMI backed by an EC2 instance store volume and attach an Amazon EBS volume for the data.
D. Launch instances with an AMI backed by an Amazon EBS volume and attach an additional EC2 instance store volume.
Question 5
A company requires a data catalog and metadata management for its AWS Cloud data sources, which include structured data from Amazon RDS and Amazon Redshift, as well as semi-structured data like JSON and XML in Amazon S3. They need a solution to regularly update the data catalog and detect changes in source metadata with minimal operational effort. Which solution is best suited?
A. Use Amazon Aurora as the data catalog and create AWS Lambda functions to gather and update metadata periodically.
B. Implement the AWS Glue Data Catalog as the central repository, employing AWS Glue crawlers to connect to data stores and regularly update the catalog.
C. Utilize Amazon DynamoDB as the data catalog with scheduled AWS Lambda functions for metadata updates.
D. Employ the AWS Glue Data Catalog and extract schemas from Amazon RDS and Redshift while using crawlers for Amazon S3.
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