A retail organization is developing a data lake solution utilizing Amazon S3 to store a large amount of data. They would like to be able to perform data exploration and discovery activities by running SQL queries on the data.Based on the output of those activities, they would like to produce complex reports accessible to a large number of users via BI applications.What AWS services should be part of their solution (SELECT TWO)?

Answer options:

A.Amazon RedShift Spectrum for the complex reporting
B.Amazon Lambda for the complex reporting
C.AWS Glue for the data discovery activities
D.Amazon Athena for the data discovery activities
E.Amazon QuickSight for the data discovery activities

Answer: A and D
Option A is CORRECT because Amazon Redshift Spectrum can be used to query data from files in Amazon S3 without loading the data into Amazon Redshift tables. Redshift Spectrum compute-intensive queries employ massive parallelism to execute very fast against large datasets.
Option B is incorrect because this is not the optimal solution as it requires custom code development and deployment using AWS Lambda.
Option C is incorrect because AWS Glue is an ETL service used to categorize and transform data.It cannot be used for querying data.
Option D is CORRECT because Amazon Athena can be used to perform ad-hoc queries on data in S3 directly using SQL syntax.
Option E is incorrect because Amazon QuickSight is a business analytics service used to build visualizations and business insights reports. It is not used for data exploration activities.
Reference:
https://docs.aws.amazon.com/athena/latest/ug/when-should-i-use-ate.html
https://docs.aws.amazon.com/redshift/latest/dg/c-using-spectrum.html