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EXAMPLE QUESTIONS
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7 Blueprints
Detect data anomalies in new S3 files with DuckDB SQL and email a CSV of the bad rows.
Watch a CloudWatch backlog metric and fire an EMR Serverless Spark job only when work is pending.
Trigger a Python data pipeline automatically whenever a new file lands in an Amazon S3 bucket.
Run a Glue ETL job, validate the output with Athena, then cache the headline KPI in DynamoDB.
Sync AWS resource metadata into Postgres with CloudQuery, then flag public S3 buckets with SQL.
Ingest JSON from Amazon S3, unify and curate it with DuckDB, and register every step as governed dataset assets with full lineage.
Trigger on new S3 files, batch load each one into Postgres in parallel, transform with dbt, and alert Slack on failure.