Blog

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 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 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 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 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…

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 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 12, 2026

Gartner opened the Data & Analytics Summit 2026 with a memorable metaphor. The keynote framed the current moment as a raft ride through a roaring, treacherous river. The river represented AI. Fast-moving. Powerful. Difficult to control. The message was clear.…

Updated March 11, 2026

A logistics company deploys an AI agent to monitor inventory and automatically trigger reorders. The model is solid. The prompts are well-engineered. The agent connects to their analytics environment and starts running. Three weeks in, it fires a reorder for…

Updated March 5, 2026

I've been in the BI and data space long enough to recognize when something fundamental shifts. Denny Lee and I first worked together when he was at Microsoft on SQL Server Analysis Services (SSAS), and I was a customer building…

Updated February 25, 2026

Most enterprise AI conversations still center on prompts, whether through chat interfaces, copilots, or question-answer workflows. But the highest-value AI agents don’t wait for someone to ask a question. They monitor signals, detect thresholds, and trigger actions. These are headless…

Updated February 24, 2026

Recently, while debating my next career chapter with a close friend, they highlighted something I had almost begun to take for granted: the most important work our civilization is doing right now is tied to the advancement of AI. It…

Updated February 20, 2026

Many teams assume they’re doing agentic analytics because they support text-to-SQL or chat-based BI. And while conversational BI does change how questions are asked, it doesn’t go so far as to change how decisions are made. It’s like transitioning from…