โ๏ธAWS Machine Learning BlogโขStalecollected in 9m
Agentic AI Analytics on SageMaker with Q & Athena
๐กAgentic AI turns SageMaker into self-service analytics powerhouse โ query lakes without SQL.
โก 30-Second TL;DR
What Changed
Amazon Q agentic AI enables self-service data analytics on SageMaker.
Why It Matters
Empowers AI practitioners to query data lakes conversationally, reducing SQL expertise needs and accelerating insights in ML pipelines.
What To Do Next
Build an Amazon Q agent in SageMaker Studio to query your S3 data lake via natural language.
Who should care:Developers & AI Engineers
Key Points
- โขAmazon Q agentic AI enables self-service data analytics on SageMaker.
- โขLeverages S3 storage with SageMaker and AWS Glue for lakehouse setup.
- โขAthena supports serverless SQL queries on S3 Table, Iceberg, Parquet formats.
- โขTransforms traditional analytics into agent-driven workflows.
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Original source: AWS Machine Learning Blog โ