Reference Overview
Key takeaway
The data and AI reference section provides practical tools teams can apply immediately. It includes delivery checklists for strategy, governance, platform, and AI model readiness, and a glossary of operational KPIs for data platforms, data products, and MLOps. Teams use them to check quality, reliability, and governance and keep data and AI delivery on track.
The Reference section provides checklists and KPIs you can use to keep data and AI delivery on track.
Featured References
Next Steps
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Frequently asked questions
What reference tools are available for data and AI delivery?
The reference section includes data and AI delivery checklists, an enterprise AI security pre-flight checklist for connecting LLMs to enterprise data, a glossary of operational KPIs for data platforms, data products, and MLOps, and a white paper on security and governance limitations in self-hosted analytics platforms.
When should teams use data and AI delivery checklists?
Use delivery checklists at three points: project kickoff, before launch, and during quarterly reviews. At kickoff they confirm strategy and governance basics are in place, before launch they verify platform and model readiness, and quarterly reviews catch gaps that emerge as data, teams, and priorities change.
