Session Outline
This talk will share practices on how to monitor data quality at all stages of the software development lifecycle. At Tenable, our exposure management data platform uses Snowflake AI Data Cloud to power our customer facing applications and Monte Carlo to drive data + AI observability across our modern data platform. For SaaS paying customers, data quality is table stakes. A deliberate approach to data quality is necessary to ensure consistent data experience for our application builders and customers alike.
Key Takeaways
- It starts with your SDLC. The earlier you find issues, the cheaper they are to fix.
- Data pipeline observability: monitoring data in flow.
- Data + AI Observability: data stores are a big bundle of state and how that state changes needs to be understood and monitored, particularly in the age of AI
