Construyendo Lagos de Datos y Analíticos en AWS + Datos Abiertos
summary
Shows a live end-to-end data lake built on Amazon S3 with metadata in AWS Glue, automated crawlers and ETL that write Parquet, cataloged and queried by Amazon Athena, with optional Redshift/EMR/Kinesis and ML via SageMaker; a demo ingests public movie ratings, runs a Glue Python job, produces three Parquet tables, and answers a million-row join in under four seconds, all assembled in about 15 minutes and secured with Lake Formation for access control.
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chapters (14)
- 0:00Start
- 2:06Traditional Data Warehouse Architecture
- 5:09Data Leaks in the Cloud
- 6:25What Is a Data Leak
- 15:20Redshift Spectrum
- 16:31Technologies behind Athena
- 16:58Emr
- 22:44Sage Maker Studio
- 24:07Lake Formation
- 25:19Aws Console
- 25:42Create a Bucket
- 30:29Live Demo
- 31:51Create the Script
- 40:41Create a New Data Set
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