Systems | Development | Analytics | API | Testing

Don’t let the "AI iceberg" sink your IP Most leaders only focus on the flashy models at the surface, but the real value—and the risk—is what’s underneath. Tony Seale and Jessica Talisman reveal why turning AI back onto your own data infrastructure to build connected ontologies is the key to security. This semantic foundation is the core of Agentic Analytics, ensuring your insights are grounded in your specific business logic rather than generic LLM guesses.

Is your AI-driven "autonomous enterprise" a reality or a peak-of-inflated-expectations dream? Most organizations rush toward the end state of AI agents without doing the foundational work of defining how their data actually relates through a robust ontology. In this episode of The Data & AI Chief, we sit down with Tony Seale, Founder of The Knowledge Graph Guys, and Jessica Talisman, CEO and Founder of The Ontology Pipeline. We break down why the "lost art" of data modeling and the development of semantic layers are the secret weapons for scaling Agentic Analytics.

Learn why an organization’s ontology, a structured framework for how a business defines, connects, and makes sense of its data and knowledge, is the most valuable and most overlooked asset in any AI strategy. Jessica Talisman, CEO and Founder of The Ontology Pipeline, and Tony Seale, Founder of The Knowledge Graph Guys, break down what it actually takes to build trusted AI, covering everything from semantic layers and knowledge graphs to why provenance is non-negotiable.

Are you spending too much time hunting down data assets across your cluster? Manually tracking every table and model shouldn't be a full-time job—it's time to let your metadata do the heavy lifting. In this walkthrough, we show you how to generate a comprehensive list of every table and model in your system to give you the clarity needed for optimization and cleanup. By leveraging CS tools to execute metadata commands and navigating the ts-metadata-objects folder, you can identify critical logical tables and capture object subtypes with precision.

Tired of manual reporting workflows holding back your team? Learn how to scale your data distribution by mastering Liveboard exports through both the UI and ThoughtSpot’s REST API v2. In this walkthrough, we dive into the technical details of capturing specific tabs and formatting reports in high-quality PDF and XLSX. We’ll show you how to use identifiers and filters to customize insights—like a brand manager automating reports specifically for Coca-Cola—so your stakeholders get exactly what they need, when they need it.

Why do most BI tools feel like they were built for someone else? Because they were built to be general—and "general" doesn't cut it in the Agentic era. At our March Spotlight, ThoughtSpot CMO Micheline Nijmeh introduces the unveiling of Spotter for Industries: AI designed from the ground up to understand your specific metrics, workflows, and priorities. We’re moving past the hype to deliver real business results.

This is one question a banking team can ask Spotter right now, "Which customers are likely to churn based on declining balance activity over the last 90 days?" No ticket to the data team, no waiting on a dashboard build, and no SQL. Just a plain-language question and an answer your retention team can act on today. That's the shift from reactive reporting to agentic analytics. Your data answers back.

Your customer service team flags churn risk in a quarterly review. Your product team spots low adoption in a dashboard two weeks later. By the time anyone acts, the customer is already gone. The delay is the real cost of fragmented analytics in software companies. Spotter for Software and Tech surfaces those signals in real time. It connects product usage, sales pipeline, and customer health data so that teams can ask questions like “Which accounts dropped engagement this month and what changed?” This way, they get answers quickly and can act immediately.

Is AI a tool or a threat? Wharton Professor Stefano Puntoni explains why "self-preservation mode" is killing AI adoption in the workplace. Puntoni joins Cindi Howson (The Data Chief host) & breaks down why AI isn't a strategy—it's a tool that requires a "meet in the middle" approach. To succeed, leaders must provide the vision and resources, while empowering workers to co-create the roadmap.

Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact.