Data, Analytics and AI Governance

Data, analytics and AI governance is perhaps the most important yet challenging aspect of any data and AI democratisation effort. For data analytics and AI, you likely use separate systems — data warehouses for BI and data lakes for AI — creating silos with different governance models. Beyond files and tables, assets like dashboards, ML models, and notebooks each have unique permission controls, making consistent access management challenging. The problem gets bigger when your data assets exist across multiple clouds with different access management solutions. What you need is a unified approach to simplify governance for all your data on any cloud.