Which formats can AWS Glue DataBrew output data in?

Which formats can AWS Glue DataBrew output data in?

• A. Only XML and PDF
• B. CSV, JSON, and Parquet
• C. Text and HTML
• D. Only Avro format

Answer: (B)

AWS Glue DataBrew supports outputting data in CSV, JSON, and Parquet formats. Each of these formats is commonly used for data storage and exchange. CSV (Comma-Separated Values) is widely utilized for its simplicity and ease of use in many applications, particularly for tabular data. JSON (JavaScript Object Notation) is popular for structured data storage and APIs, enabling easy integration with web applications and programming languages. Parquet, on the other hand, is an efficient columnar storage format that is optimized for use with big data processing frameworks like Apache Spark, allowing for better performance in analytical queries. The ability to output data in these formats means that users can easily work with their cleaned and transformed data in various downstream processes, such as analytics, machine learning, and integration with other AWS services. This versatility enhances the overall usability of AWS Glue DataBrew within data workflows. The other formats mentioned in the options do not match the capabilities of DataBrew, as the tool does not support XML, PDF, Avro, or plain text formats for output.

AWS Glue DataBrew supports outputting data in CSV, JSON, and Parquet formats. Each of these formats is commonly used for data storage and exchange.

CSV (Comma-Separated Values) is widely utilized for its simplicity and ease of use in many applications, particularly for tabular data. JSON (JavaScript Object Notation) is popular for structured data storage and APIs, enabling easy integration with web applications and programming languages. Parquet, on the other hand, is an efficient columnar storage format that is optimized for use with big data processing frameworks like Apache Spark, allowing for better performance in analytical queries.

The ability to output data in these formats means that users can easily work with their cleaned and transformed data in various downstream processes, such as analytics, machine learning, and integration with other AWS services. This versatility enhances the overall usability of AWS Glue DataBrew within data workflows.

The other formats mentioned in the options do not match the capabilities of DataBrew, as the tool does not support XML, PDF, Avro, or plain text formats for output.