Back to blog
[Conference recap]
Snowflake World Tour Toronto: Data Apps, AI, and Governance
What clicked most: shipping AI/data features with clear SLIs, stronger access controls, and repeatable release patterns.
- Format
- Conference recap
- Event
- Snowflake World Tour
- Focus
- Data apps, AI, governance
[01]
Quick highlights
- Native App patterns help package data products safely.
- LLM workloads need latency/cost/drift thresholds defined up front.
- Observability + least-privilege access are core to trusted reporting systems.
[02]
Sessions that stuck
Snowflake Native Apps
Packaged distribution + access controls for safer external/internal data delivery.
Native Apps / GovernanceLLM workloads on Snowflake
Telemetry and budget controls keep AI-assisted features reliable.
AI / ObservabilitySecure data sharing
Lineage and audit trails are mandatory for regulated or high-risk reporting.
Security / Compliance[03]
What I am applying
- Define SLIs for AI-assisted reporting: latency, cost per request, drift thresholds.
- Strengthen data lineage and access controls before adding new data feeds.
- Pilot versioned package + rollback patterns for internal data products.
[04]
Scenes from the tour
GDG DevFest Toronto: weekend of AI, mobile, and cloud
