AWS Certified Solutions Architect Associate SAA-C03 Practice Question
A company needs to convert large volumes of raw data, coming in different formats such as CSV, JSON, and XML, into a homogenous form suitable for analytical query processing in their cloud-based data warehouse. The solution must be serverless to handle fluctuating workloads, scale on-demand, and eliminate the overhead of infrastructure management. Which service should the company implement to automate the data conversion process while ensuring scalability and cost-efficiency?
Amazon Simple Storage Service (Amazon S3) with custom processing functions
The service that fits the requirements of being serverless and capable of handling fluctuating data processing workloads is AWS Glue. It allows the automation of converting data into a consistent and query-optimized format without the need to manage the underlying infrastructure. It supports various data formats and has built-in capabilities for data cleansing and transformation, which makes it a suitable choice for preparing data for analytics in a data warehouse. Other options like AWS Data Pipeline offer managed ETL service but are not serverless, and using Amazon EC2 would require managing servers. AWS Lambda is serverless but is not primarily designed for ETL workflows and may not be as robust or straightforward when dealing with complex and large-scale data transformation as AWS Glue.
Ask Bash
Bash is our AI bot, trained to help you pass your exam. AI Generated Content may display inaccurate information, always double-check anything important.
What are the key features of AWS Glue that make it suitable for data transformation?
Open an interactive chat with Bash
How does AWS Glue ensure scalability and cost-efficiency?
Open an interactive chat with Bash
What is the difference between AWS Glue and other data processing options like AWS Lambda or Amazon EC2?