AWS Data Processing Plan

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Plans governed data-processing workflows across AWS Glue, EMR, EMR Serverless, Athena, S3, and IAM. Produces catalog, compute, orchestration, data-quality, encryption, cost, and observability decisions with read-only discovery first and explicit approval before resource changes.

awsglueemrathenaetldata-engineeringgovernance

Casos de uso

  • 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

Prompt de ejemplo

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.

Modelos recomendados

gpt-5-6-solclaude-opus-5gemini-3-6-flash

Herramientas compatibles

claude-codecursorkirogemini-cliany

Modalidades

Entrada: text, code, file
→
Salida: text, code

Skills relacionadas

data-pipeline-builderiam-policy-reviewercloud-cost-optimizer

Autor

OpenModels Community

@openmodelsrun

Editor

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OpenModels Community

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