Which solution will meet these requirements?

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In: SAA-C03
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A company hosts a data lake on Amazon S3.The data lake ingests data in Apache Parquet format from various data sources.The company uses multiple transformation steps to prepare the ingested data.The steps include filtering of anomalies, normalizing of data to standard date and time values, and generation of aggregates for analyses.The company must store the transformed data in S3 buckets that data analysts access.The company needs a prebuilt solution for data transformation that does not require code.The solution must provide data lineage and data profiling.The company needs to share the data transformation steps with employees throughout the company.

Which solution will meet these requirements?

Configure an AWS Glue Studio visual canvas to transform the data. Share the transformation steps with employees by using AWS Glue jobs.

Configure Amazon EMR Serverless to transform the data. Share the transformation steps with employees by using EMR Serverless jobs.

Configure AWS Glue DataBrew to transform the data. Share the transformation steps with employees by using DataBrew recipes.

Create Amazon Athena tables for the data. Write Athena SQL queries to transform the data. Share the Athena SQL queries with employees.

Explanations:

AWS Glue Studio is a visual interface for building ETL workflows, but it still requires code to define jobs. While it provides some lineage and transformation capabilities, it doesn’t fully meet the requirement of a prebuilt solution that doesn’t require code.

Amazon EMR Serverless is more suited for big data processing with frameworks like Apache Spark. It requires code (e.g., Spark jobs) for transformations, which contradicts the requirement for a no-code solution.

AWS Glue DataBrew is a fully managed, no-code data preparation tool that supports transformations like filtering, normalization, and aggregation. It also provides data lineage and profiling capabilities, and transformation steps (recipes) can be easily shared with others.

Amazon Athena is a query service for analyzing data in S3 using SQL. While it can transform data with SQL queries, it doesn’t offer the no-code, visual transformation capabilities, data lineage, or profiling required by the company. It also doesn’t natively support sharing transformation steps like DataBrew recipes.

2026-03-16

2 Comments

  1. Jennifer
    Author

    I design that the answer is:
    Configure AWS Glue DataBrew to transform the data. Share the transformation steps with employees by using DataBrew recipes.

  2. Stephen
    Author

    I measure that the answer is:
    Configure AWS Glue DataBrew to transform the data. Share the transformation steps with employees by using DataBrew recipes.

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