Agentic AI needs a foundation you build—not a tool you buy
Agentic AI fails without the right data foundation. Learn the four capabilities your data strategy needs to succeed with autonomous automation.
Building trusted data products at speed & scale with AI in 2026
Learn how advancements in automation and AI are transforming data products creation by increasing speed, reuse, value, and trust.
data foundation
From blueprint to business value: How to build an AI-ready data foundation
Learn how to build an AI-ready data foundation that transforms blueprints into business value. Discover proven strategies for trusted data products and AI success.
Building AI for AI: How trust models and data marketplaces are changing the game
Learn how AI for AI transforms data management with autonomous data products, trust models, and data marketplaces to deliver AI initiatives that succeed.
Quest’s vision for a converged data platform for AI – Fully aligned with Gartner
Quest Software’s erwin Data Management Platform already meets Gartner’s 2028 vision: unified metadata, governance & multimodel support for AI success.
data products
The quick win approach: Your trusted data products transformation roadmap
Drive AI success with trusted data products in 90 days. Learn how to boost quality, governance and scalability across your organization.
The hidden AI tax: Why there’s an 80% AI project failure rate
Enterprises are facing an 80% AI project failure rate, costing billions. Discover the hidden barriers causing AI failure and how to avoid them.
Data lakehouse architecture: Ensure AI can understand and trust your data
To scale AI with confidence, your data lakehouse architecture needs strong modeling and governance for structure, trust and traceability.
Data lakehouse strategy: Build a foundation for real-time, AI-ready insights
Explore a practical data lakehouse strategy to support real-time analytics, AI readiness and scalable architecture.
Snowflake Summit: Key takeaways from a week of AI, data and dog robots
Here are the key takeaways from Snowflake Summit 2025 – the emphasis was on AI integration into every stage of the data lifecycle.
Why data modeling is a MUST for your Oracle to Snowflake migration
Learn why data modeling is essential for your Oracle to Snowflake migration and how to modernize with confidence.
The ROI of proactive database observability: Four ways to transform your business
Learn how database observability drives ROI and resilience by improving performance, reducing costs, and minimizing risk.