Uploaded May 2026 | Updated September 2026, 2 weeks ago
Join us to see what happens when your IDE becomes your entire data workflow.
Data practitioners today bounce between notebooks, consoles, CLI tools, and dashboards just to go from idea to deployed pipeline — and every context switch costs time and focus. In this session, we'll demo how Kiro, connected to a cloud data environment via SageMaker Unified Studio's Local IDE feature, collapses that multi-tool, multi-tab reality into a single, prompt-driven experience. You'll watch us go from a raw dataset to a governed, queryable asset — all from one IDE, one conversation — while SageMaker handles compute, governance, and infrastructure behind the scenes. Whether you're a data engineer, data scientist, or analyst, you'll walk away knowing how to bring agentic development to your AWS data stack without leaving the tools you already love.
Join us to see what happens when your IDE becomes your entire data workflow.
Data practitioners today bounce between notebooks, consoles, CLI tools, and dashboards just to go from idea to deployed pipeline — and every context switch costs time and focus. In this session, we'll demo how Kiro, connected to a cloud data environment via SageMaker Unified Studio's Local IDE feature, collapses that multi-tool, multi-tab reality into a single, prompt-driven experience. You'll watch us go from a raw dataset to a governed, queryable asset — all from one IDE, one conversation — while SageMaker handles compute, governance, and infrastructure behind the scenes. Whether you're a data engineer, data scientist, or analyst, you'll walk away knowing how to bring agentic development to your AWS data stack without leaving the tools you already love.
