A company needs to quickly make sense of a large amount of data and gain insight from it. The data is in different formats, the schemas change frequently, and new data sources are added regularly. The company wants to use AWS services to explore multiple data sources, suggest schemas, and enrich and transform the data. The solution should require the least possible coding effort for the data flows and the least possible infrastructure management.
Which combination of AWS services will meet these requirements?

A. Amazon EMR for data discovery, enrichment, and transformation
Amazon Athena for querying and analyzing the results in Amazon S3 using standard SQL
Amazon QuickSight for reporting and getting insights
B. Amazon Kinesis Data Analytics for data ingestion
Amazon EMR for data discovery, enrichment, and transformation
Amazon Redshift for querying and analyzing the results in Amazon S3
C. AWS Glue for data discovery, enrichment, and transformation
Amazon Athena for querying and analyzing the results in Amazon S3 using standard SQL
Amazon QuickSight for reporting and getting insights
D. AWS Data Pipeline for data transfer
AWS Step Functions for orchestrating AWS Lambda jobs for data discovery, enrichment, and transformation
Amazon Athena for querying and analyzing the results in Amazon S3 using standard SQL
Amazon QuickSight for reporting and getting insights