AWS Data Processing Plan

Anwendungsfälle

• Choosing between Glue, EMR, EMR Serverless, and Athena
• Planning governed catalogs and ETL workflows
• Auditing data-processing IAM and encryption
• Estimating cost and operational controls before rollout

Design an AWS data-processing plan for this workload.

Sources: [systems, formats, sizes, arrival pattern]
Consumers: [queries, dashboards, ML, exports]
Constraints: [latency, region, retention, compliance, budget]

Produce:
1. A service-selection decision for Glue, EMR, EMR Serverless, Athena, and S3.
2. Catalog, partitioning, schema-evolution, and data-quality rules.
3. Read-only discovery steps before any mutation.
4. IAM, encryption, network, and sensitive-data controls.
5. Cost model, quotas, metrics, and failure recovery.
6. A staged implementation plan with acceptance tests.

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