MLA-C01 Question 69
Single answerYou are working as an AWS Certified Machine Learning Engineer for an e-commerce platform. The platform generates large volumes of semi-structured transaction data daily, and you need to clean, normalize, and transform this data for a machine learning model. Furthermore, the business team requests an interactive tool to visually inspect and validate the data transformation steps. Which AWS service or combination of services is best suited for this task?
- A
AWS SageMaker Data Wrangler
- B
AWS Glue
- C
AWS Glue DataBrew
- D
AWS Lambda
Show answer and explanation
Correct answer: C
Explanation
AWS Glue DataBrew is the best choice for this scenario because it provides an interactive, no-code interface for cleaning and transforming data, as well as the ability to visually validate the transformation steps. While other services like AWS Glue and SageMaker Data Wrangler can be used for data preparation, they lack the specific interactive and visual capabilities needed for this task.
- A. Incorrect.
AWS SageMaker Data Wrangler is a great tool for data preparation and visualization, but it is better suited for smaller datasets or when tightly integrated with SageMaker workflows. It is less optimal for interactive exploration of large datasets from semi-structured sources.
- B. Incorrect.
AWS Glue is a serverless data integration service that can process and transform large datasets, but it does not offer an interactive, visual interface for data inspection and validation.
- C. Correct.
AWS Glue DataBrew is specifically designed to clean and transform data with a visual, interactive interface. It is well-suited for this use case as it allows you to easily inspect and validate data transformation steps while handling semi-structured data.
- D. Incorrect.
AWS Lambda is a serverless compute service that can be used for lightweight data processing tasks, but it is not designed for interactive data exploration or transformation.