Dave Mariani

Dave Mariani LinkedIn Profile

Dave is the founder of AtScale and is the Chief Technology Officer. Prior to AtScale, he was VP of Engineering at Klout & at Yahoo! where he built the world’s largest multi-dimensional cube for BI on Hadoop. Mariani is a Big Data visionary & serial entrepreneur.

March 17, 2026

Why Moving Data for BI and AI Creates Architecture Problems

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…

March 12, 2026

Hits and Misses from Gartner Data & Analytics Summit 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.…

February 25, 2026

Headless AI Agents Are Already Here and They’re Where the ROI Is

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…

February 20, 2026

Why Agentic AI Fails Without a Semantic Layer

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…

February 17, 2026

The Hidden Costs of Letting People “Talk to Data” with AI

Conversational BI pilots succeed because they operate in constrained environments. A dozen users, curated datasets, predictable query patterns. When AI agents enter the picture, everything breaks. Gartner forecasts that more than 40% of agentic AI projects will be abandoned by…

February 3, 2026

Why Most Enterprise AI Projects Fail (and How to Make Them Work at Scale)

Most enterprise AI projects follow a familiar pattern. Successful demos lead to promising pilots. Executives commit budgets to scale the initiative across departments. Then the wheels come off. Despite $30-40B in enterprise investment in GenAI, MIT’s Project NANDA found roughly…

January 29, 2026

Why Context Became the Most Critical Layer in Enterprise AI

I recently sat down with Juan Sequeda, Principal Researcher at ServiceNow and co-author of Designing and Building Enterprise Knowledge Graphs, to discuss what's happening in enterprise data and AI. Listen to the full podcast episode here. Juan brings a unique…

January 21, 2026

The Hidden Cost of Semantic Drift in Enterprise AI

Three teams ask the same question: "What was our gross margin last quarter?" Finance's dashboard shows it’s 30%. Sales’ margin reports show 32%. The AI copilot reports 31%. Which one's correct? Technically, all of them. Each system defines "gross margin"…