AWS Certified Data Engineer - Associate
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You are working on a data pipeline for a retail company that needs to process and analyze customer transaction data from various sources, including online and in-store purchases. The pipeline should be able to handle both batch and real-time data. Which AWS services would you use to create this pipeline, and how would you configure them to meet the requirements?
A
Use Amazon Kinesis for real-time data streaming, AWS Glue for ETL processing, and Amazon Redshift for data warehousing. Configure Kinesis to capture real-time data, Glue to process both batch and real-time data, and Redshift to store and analyze the processed data.
B
Use Amazon S3 for data storage, AWS Lambda for serverless computing, and Amazon QuickSight for data visualization. Configure Lambda to process customer transaction data stored in S3, and QuickSight to visualize the processed data.
C
Use AWS Data Pipeline for scheduling and workflow management, AWS Glue for ETL processing, and Amazon Redshift for data warehousing. Configure Data Pipeline to schedule Glue jobs based on dependencies, and Glue to process customer transaction data.
D
Use Amazon Kinesis Data Firehose for real-time data ingestion, AWS Glue for ETL processing, and Amazon QuickSight for data visualization. Configure Firehose to capture real-time data, Glue to process the data, and QuickSight to visualize the processed data.