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Configuración de AWS S3 e IAM\nCrear un bucket de S3 llamado etl-source-data para almacenar los datos sin procesar.\nCrear otro bucket etl-processed-data para los datos transformados.\nCrear un usuario IAM con permisos para S3 (s3:PutObject, s3:GetObject, etc.).\nConfigurar credenciales en ~/.aws/credentials o usar variables de entorno.\n### 🔹 2. Subir un Dataset a S3\nDescargar un dataset público (por ejemplo, sobre ventas, clima, etc.).\nSubirlo manualmente a etl-source-data o usar un script Python con Boto3.\n### 🔹 3. Desarrollo del Script ETL con Python\nEl script debe:\n\nExtraer el archivo CSV desde S3.\nTransformar los datos (limpieza, conversión de tipos, agregaciones).\nCargar los datos procesados en otro bucket o en RDS.\n### 🔹 4. Automatización con AWS Lambda (Opcional)\nSubir el script a AWS Lambda.\nConfigurar un trigger para ejecutarlo cada vez que se suba un nuevo archivo a S3.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftuni56%2Fetl_miniproject","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftuni56%2Fetl_miniproject","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftuni56%2Fetl_miniproject/lists"}