These are some of good labs that can be tried on AWS regarding Big Data leveraging on Data Lake strategy.
Please kindly read through in here:
– simple lab: https://bit.ly/2wk6q6O
– moderate lab: https://shorturl.at/gk037
– longer lab (the diagram below): https://github.com/aws-samples/amazon-serverless-datalake-workshop (it will create custom page, i.e: https://s3.us-east-1.amazonaws.com/starxforce-ecommerce-datalake-ingestionbucket-ip2te8auqgxv/instructions/instructions.html)

Note: This sql code below is just my quick demo for lab purpose (please ignore this):
=== athena ===
SELECT state,
request as page,
count(request) AS totalviews
FROM zipcodesdata z, joindatasets m
WHERE z.zipcode = m.zip
GROUP BY state, request
ORDER BY state
=== redshift spectrum ===
SELECT count(*) as TotalCount FROM "weblogs"."useractivity" where request like '%Dogs%';
SELECT username, COUNT(timestamp)
FROM local_weblogs.useractivity
GROUP BY username;
SELECT username, COUNT(timestamp)
FROM weblogs.useractivity
GROUP BY username;
SELECT ua.username, first_name, last_name, COUNT(timestamp)
FROM local_weblogs.useractivity ua
INNER JOIN weblogs.userprofile up ON ua.username = up.username
GROUP BY ua.username, first_name, last_name limit 100;
SELECT * FROM local_weblogs.useractivity_byuser LIMIT 100;
Kind Regards,
Doddi Priyambodo