On Day 1 we collected data, and on Day 2 we cataloged and transformed it with Glue. Now it's time to read and understand the data. Before building a model, a data scientist must examine the data closely. "What's the feature distribution? Are there missing values? How does it relate to the target?" — this is EDA (Exploratory Data Analysis).
Today we look at Athena for directly querying the data lake, the Redshift data warehouse, and the fundamentals of EDA, the starting point for ML.
Athena is a service that queries data stored in S3 using serverless SQL. Built on Presto/Trino, it requires no cluster provisioning