A data engineer at a manufacturing firm is developing a platform for analyzing huge amounts of unstructured data. The da
Posted: Thu Jul 21, 2022 10:00 pm
A data engineer at a manufacturing firm is developing a platform for analyzing huge amounts of unstructured data. The data engineer must fill an Amazon Redshift star schema with well-structured data.
Which architectural approach is the most efficient for this purpose?
A. Transform the unstructured data using Amazon EMR and generate CSV data. COPY the CSV data into the analysis schema within Redshift.
B. Load the unstructured data into Redshift, and use string parsing functions to extract structured data for inserting into the analysis schema.
C. When the data is saved to Amazon S3, use S3 Event Notifications and AWS Lambda to transform the file contents. Insert the data into the analysis schema on Redshift.
D. Normalize the data using an AWS Marketplace ETL tool, persist the results to Amazon S3, and use AWS Lambda to INSERT the data into Redshift.
Which architectural approach is the most efficient for this purpose?
A. Transform the unstructured data using Amazon EMR and generate CSV data. COPY the CSV data into the analysis schema within Redshift.
B. Load the unstructured data into Redshift, and use string parsing functions to extract structured data for inserting into the analysis schema.
C. When the data is saved to Amazon S3, use S3 Event Notifications and AWS Lambda to transform the file contents. Insert the data into the analysis schema on Redshift.
D. Normalize the data using an AWS Marketplace ETL tool, persist the results to Amazon S3, and use AWS Lambda to INSERT the data into Redshift.