Blog

Updated April 9, 2026

AI is shifting the center of gravity in data architecture from raw data to a governed business context. The last decade of data architecture was shaped by data gravity. The next decade will be shaped by context gravity. The cloud…

Updated April 6, 2026

For years, data governance was viewed as a background concern. Teams had bigger priorities to tackle and more pertinent problems to solve. Then AI agents came into the fold and started generating business decisions from inconsistent data, and suddenly, governance…

Updated April 6, 2026

As AI agents move beyond the helpful copilot phase and into more powerful applications, enterprises are responding with global adoption. Agentic AI is everywhere, from analytics and finance to customer service and operations. It's changing how organizations go from asking…

Updated April 1, 2026

The semantic layer has moved from niche infrastructure to a boardroom priority. Snowflake announced one. Databricks announced one. Google repositioned Looker as one. Microsoft repositioned Power BI as one. This is genuinely good news. As ISG analyst Matt Aslett observed…

Updated March 30, 2026

Over the past year alone, AI tools that once surfaced insights and handed them to a human for action have begun carrying out those actions themselves. Sixty-two percent of organizations are now experimenting with AI agents, according to McKinsey's latest…

Updated March 27, 2026

Enterprise analytics was never just about data. It was about trust and confidence, getting the right people the right information so they could make intelligent decisions and keep things moving forward. The BI stack was made for that purpose, and…

Updated March 26, 2026

Autonomous AI agents, which are systems designed to accomplish tasks and goals independently without human oversight, have become integral across a wide range of use cases, spanning from customer service to supply chain management. It's no surprise that, as regulatory…

Updated March 26, 2026

Most enterprises have already standardized where their data lives. What they haven’t standardized is how that data is interpreted. Power BI and Excel users still rely on a workaround: moving data out of Snowflake into extracts, cubes, or Microsoft Fabric…

Updated March 17, 2026

In modern data architectures, analytics tools often replicate data from the warehouse into secondary systems to improve performance. While this can speed up dashboards, it introduces new problems: duplicated datasets, inconsistent metrics, fragmented governance, and rising cloud costs. Modern analytics…

Updated March 16, 2026

For a long time, enterprise analytics centered around building dashboards, running scheduled reports, and relying on the right person to ask the right question at the right time. That model is changing. Autonomous AI agents can now look through data…