AWS Certified Machine Learning Engineer - Associate MLA-C01 — Topic 1 Question 108

Question

An ML engineer needs to merge and transform data from two sources to retrain an existing ML model. One data source consists of .csv files that are stored in an Amazon S3 bucket. Each .csv file consists of millions of records. The other data source is an Amazon Aurora DB cluster. The result of the merge process must be written to a second S3 bucket. The ML engineer needs to perform this merge-and-transform task every week. Which solution will meet these requirements with the LEAST operational overhead?

Accepted Answer

Correct answer: B. The correct answer is B. Option B: Create a weekly AWS Glue job that uses the Apache Spark engine. Use DynamicFrame native operations to merge and transform the data. AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data.

AWS Certified Machine Learning Engineer - Associate MLA-C01 — Question 108