Questions and Answers
What primary function does AWS Glue DataBrew allow users to perform without writing any code?
Which data store can AWS Glue DataBrew connect to directly for data preparation?
What feature does the COUNT_DISTINCT function provide within AWS Glue DataBrew?
Why is using a PySpark script for counting distinct entries not favorable compared to AWS Glue DataBrew?
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What is the role of AWS Glue Crawlers in relation to data preparation?
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Which of the following tasks is NOT facilitated by AWS Glue DataBrew?
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What is a significant advantage of using AWS Glue DataBrew over AWS Lambda for data processing?
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Which statement about using AWS Glue DataBrew for ongoing analysis is correct?
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Study Notes
AWS Glue DataBrew Overview
- User-friendly tool designed for data preparation without any coding required.
- Facilitates cleaning, transforming, and profiling data directly from sources like Amazon S3, Amazon Redshift, and Amazon RDS.
- Enables data engineering teams to perform tasks efficiently, such as merging fields and aggregating counts.
Key Features
- Utilizes the COUNT_DISTINCT function to easily identify unique customers with minimal effort.
- Allows users to save and reuse recipes and results for ongoing analysis of datasets.
Comparison with Other Options
- Constructing a recipe with AWS Glue DataBrew is the most efficient method for calculating distinct counts.
- Writing a PySpark script in Amazon EMR Serverless is less optimal since it requires coding, contrasting with DataBrew's no-code approach.
- Using AWS Glue Crawlers to infer schema and then writing a Spark job to perform unique customer counts is more complex due to the need for custom coding and increased effort.
- Configuring an AWS Lambda function to execute Python scripts for processing large files poses challenges with execution time and memory limitations, complicating task management.
Challenges in Alternatives
- AWS Glue Crawlers discover and profile source data but add overhead by necessitating custom transformations through Spark jobs.
- AWS Lambda is limited in handling large files (up to 3GB), requiring careful resource management and potentially increasing operational complexity.
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Description
This quiz covers the essentials of AWS Glue DataBrew, a no-code tool that simplifies data preparation tasks such as cleaning, transforming, and profiling data. It highlights key features like the COUNT_DISTINCT function and compares it with coding-dependent methods, emphasizing its efficiency for data engineering teams.
