Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 87 discussion

🔑 Keyword: Process mixed file types with AWS Glue DataBrew & store for AWS Glue ✅ Correct Answer: A. Use DataBrew to process the existing S3 folder. Store the output in Apache Parquet format. Why? AWS Glue performs best with Parquet because it is optimized for analytical queries. No need to split data into separate folders—DataBrew can handle mixed file types. Why Others Are Wrong? ❌ B. "AWS Glue Parquet format" is not a valid term. Apache Parquet is the correct format. ❌ C & D. Separating files into different folders is unnecessary—DataBrew can process multiple formats in a single folder.

C implies that you have to re-organize all files (1 TB is a lot). This means a lot of work. For me is A, less performance but without initial overhead of organization

✅ Explanation: Problem Summary: The data in S3 is mixed file formats: CSV, JSON, XLSX, and Parquet — all in one folder. You need to use AWS Glue DataBrew to process the data. The processed data must be stored in S3 for AWS Glue to consume later. Key Considerations: DataBrew Input Requirements: DataBrew datasets must be in a consistent format (CSV, JSON, XLSX, or Parquet). DataBrew cannot process mixed formats in a single dataset. You must split the data by format. DataBrew Output Format: Apache Parquet is preferred for: Efficient storage Better performance with AWS Glue and other analytics tools Columnar storage benefits in querying and transformations "AWS Glue Parquet format" does not exist — this is a distractor in the answer options.

Should be A. C is incorrect because it involve separating the data by file type, which is unnecessary since DataBrew can process various file types within the same folder.

AWS Glue DataBrew can process various file formats (CSV, JSON, XLSX, Parquet) Since DataBrew can handle datasets with multiple file formats, there is no need to separate files into different folders by type. Apache Parquet is an optimal format for AWS Glue Parquet is a columnar format, which is well-suited for AWS Glue and is efficient for later analysis and ML model training. "AWS Glue Parquet format" does not exist Options B and D mention "AWS Glue Parquet format," which is incorrect. Parquet is a standard data format and is not exclusive to AWS Glue. ✅ Conclusion: Option A is the best solution because it allows DataBrew to process all files in the existing S3 folder and store the output in Apache Parquet format, which is efficient and compatible with AWS Glue. 🚀