Why should you care?

AwsVerse analytics product turns transaction data into ML features and executive dashboards.

See it live — copy this example

Run in AWS CloudShell / local AWS CLI v2, or follow the matching steps in the AWS Console (Free Tier).

aws glue start-crawler --name awsverse-curated-crawler
aws athena start-query-execution \
  --query-string 'SELECT tenant_id, SUM(amount) AS revenue FROM awsverse_curated.payments WHERE dt>=\'2026-07-01\' GROUP BY 1' \
  --work-group awsverse-analytics \
  --result-configuration OutputLocation=s3://awsverse-athena-results/

What happened?

• Glue crawler refreshes table schema; Athena SQL aggregates revenue by tenant writing results to S3 for QuickSight.
• Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

1. Land CSV/Parquet in s3://awsverse-lake/curated/.
2. Run crawler; query in Athena console.
3. Connect QuickSight to Athena dataset.
4. Add SageMaker Feature Store offline store sync.
5. Schedule crawler nightly via EventBridge.

Remember

Lake → catalog → SQL → BI. Partition S3 by date for Athena. ML endpoints on demand only.

AwsVerse insights SKU

SaaS customers buy analytics add-on.

Outcome: Athena plus QuickSight delivers tenant dashboards same day data lands.