Democratización de datos e inteligencia de negocio; Amazon QuickSight
summary
Shows an end-to-end prototype that ingests tweets via SQS and Step Functions, runs zero-shot classification on a SageMaker serverless endpoint, extracts sentiment and entities with Amazon Comprehend, geocodes with Amazon Location Service, stores results in S3 and queries them with Glue + Athena for QuickSight dashboards. Dashboards use QuickSight Q, built-in anomaly detection and forecasting, support row-level security and scale to tens of thousands of users; pipeline processes posts near-real-time (<1 min) and replaces heavy SQL Server load with an Athena/S3 decoupled architecture.
AI-written summary · about
chapters (7)
- 0:00Introduction
- 1:07Data democratization
- 13:50Amazon QuickSight benefits
- 22:23Prevsis success case
- 37:04ML integration with QuickSight
- 48:06Analysis prototype demo
- 57:30Resources and summary
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