INSIGHTS & PERSPECTIVES

Learn how active metadata and context intelligence power agentic AI. Discover a blueprint to feed autonomous agents real-time context for safe execution.

Data alone isn't enough for AI agents. Join us for the webinar to learn how an enterprise context layer equips agents with business rules and logic to take reliable action.

Learn how RAG, AI Skills, and MCP can scale your AI systems by connecting your models to real data, tools, and workflows.

Discover how to navigate AI disruption, leverage data agents, and master governance to advance your organization’s data journey.

Discover why "context" is the missing ingredient for enterprise AI agents and how to build a Trustworthy Contextual Intelligence Layer.

Explore why dimensional modeling remains the backbone of modern data architecture, and how it provides the structured context needed for reliable AI performance and trusted, high-speed analytics.

In the agentic era we’ve now entered, you don’t win by just being faster – you win by being built differently. This in-person panel discussion surfaced “in-the-trenches” insights on the hard truths of delivering AI at scale....

Master the 5 rules for testing AI apps: move beyond pass/fail tests to statistical scoring and continuous evaluation to stop hallucinations.

As you start to build a product, it’s easy to get excited about all the possibilities. Software engineers might tell you, “We can do anything!” And while that’s probably true… but they can’t do everything....

Most product teams think they’re in sync until they realize they’re all rowing in different directions. The result? Wasted budget, feature bloat, and zero impact. Here is our playbook for...

We share some best practices on ways for visualization teams to leverage AI in data analytics to scale the design and development of BI solutions.

This Fireside Chat discusses ways to measure the value of AI initiatives, especially how to clarify the value drivers for your business team.

To get beyond the AI hype, we must stop looking for problems that AI can solve, and instead anchor our approach in business fundamentals.

Mastering Data Quality provides a modern guide to building a data quality lifecycle to de-risk tech investments and drive confident decisions.

Are you tired of the endless integration nightmare that comes with enterprise AI? The Model Context Protocol (MCP) is an open-source standard designed to solve this by creating a universal blueprint for connecting AI systems to your data. In this article, we’ll walk you through how to implement it....

An effective data strategy begins with your business objectives, where every data initiative is a direct consequence of where you want to go....

Explore practical AI techniques for smarter data quality management. Learn how self-healing data systems ensure reliable AI results.

Understanding the architectural characteristics of software is crucial for building or modernizing successful applications. This guide examines the essential elements for evaluating software architecture and provides practical insights for developers, architects, and technical leaders....