DatAInnovators & Builders
Claim This Podcastby Nexla
Podcast Overview
<p><span>DatAInnovators & Builders features Chief Data Officers and data leaders sharing real strategies for conquering data complexity and building AI solutions that work. Host Saket Saurabh, CEO of Nexla, delivers practical insights on tackling data variety, moving AI from pilot to production, and making transformation actually happen.</span></p>
Language
🇺🇲
Publishing Since
11/25/2025
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Recent Episodes
June 30, 2026
Why a data catalog isn't ready for AI agents without a semantic layer
<p>What happens when a company built on 16 acquisitions tries to run on one trusted data model? At Precisely, Dave Shuman has spent six years building the data infrastructure needed to take the business from a $300M mid-market firm to a billion-dollar global software company, and the lessons from that journey cut straight to the heart of what makes or breaks an enterprise AI strategy.</p><p>Dave outlines for Saket why most AI initiatives fail before they start: organizations skip the unglamorous work of cataloging, semantic alignment, and quality observability in a rush to get to the model. He breaks down how Precisely is building the semantic layer that lets agents operate autonomously, why data governance needs to feel like a supple leather glove rather than an iron fist, and what the CDO role has to become if it wants to stay relevant in an AI-first organization.</p><p>Topics discussed:</p><ul><li><p>Why most transformative AI starts with a data catalog, not code</p></li><li><p>Building a semantic layer so agents can operate autonomously</p></li><li><p>Managing AI model overconfidence in production rollouts</p></li><li><p>Distinguishing active governance from passive governance in agentic workflows</p></li><li><p>Structuring data products across raw, component, and trusted zones</p></li><li><p>Integrating unstructured documents into structured data pipelines</p></li><li><p>What the CDO role must become in an AI-first organization</p></li><li><p>Lessons from scaling through acquisitions and closing on one set of systems</p></li></ul><p></p>
June 16, 2026
Agent management: how do you govern AI you didn't build
<p>What happens when half the room at a Gartner executive workshop raises their hand to say they've shipped AI to production and tracked ROI? Conor Jensen, Global Field CDO at Dataiku, uses that moment to reframe the entire "AI is failing" narrative and get specific about what separates the companies making it work from the ones still stuck in prototype mode.</p><p>Conor walks Saket through the compounding mistakes he sees across enterprise AI programs, from skipping legal and governance early, to misreading which problems data can actually solve, to deploying tools company-wide before proving a single use case. The conversation covers data products, agent management, the limits of code generation tools for data teams, and why the "citizen data scientist" framing has always been slightly wrong.</p><p>Topics discussed:</p><p>- Why close to half of executives at a recent Gartner workshop reported tracked AI ROI</p><p>- Engaging legal and compliance early as a speed accelerator, not a blocker</p><p>- Building a use case prioritization process as a core organizational capability</p><p>- Treating AI outputs as data products that require ongoing ownership and maintenance</p><p>- Semantic and context layers as the foundation for AI-ready data products</p><p>- Managing agents deployed out of the box in enterprise platforms versus custom-built agents</p><p>- Why code generation tools are less effective for data engineering than software development</p><p>- The meteorologist reframe: domain experts gaining new tools, not becoming data scientists</p><p>- Where 50 to 60 percent of data team backlogs can be self-served by the business</p><p>- Why predictive analytics projects hit dead ends in non-tech companies with limited data volume</p><p><br></p>
June 2, 2026
Why fixing your data beats building an AI lab?
<p>Most enterprises are racing to build AI labs while the real problem sits in their data layer. Santiago Guillotti, Chief Data and Analytics Officer at Chubb LATAM, leads a 130-person data organization and his conclusion is direct: no vendor can fix your data problems for you. AI platforms are replaceable. The data you generate is not.</p><p>Santiago outlines for Saket how GenBI is creating outsized efficiency gains in mature companies where 35 to 40% of FTEs are still tied to BI-related tasks, and where cloud migration is only the beginning of a much larger transformation.</p><p>Topics discussed:</p><ul><li><p>GenBI as an efficiency lever in mature enterprise organizations</p></li><li><p>Cloud migration from on-prem legacy systems to Azure and Databricks</p></li><li><p>Building data teams differently in startups vs. large regulated companies</p></li><li><p>Hiring for cultural fit across Latin America, Asia, and the US</p></li><li><p>Scaling from 10-person to 100-person data organizations</p></li><li><p>AI's impact on data engineering roles and intern programs</p></li><li><p>Why data, not AI platforms, is the real competitive advantage</p></li><li><p>Three pillars of AI transformation in the insurance sector</p></li><li><p>Automating end-to-end claims flows with conversational AI</p></li><li><p>Getting POCs approved in slow-moving regulated industries</p></li></ul><p></p>
16 total episodes available
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- What is DatAInnovators & Builders?
<p><span>DatAInnovators & Builders features Chief Data Officers and data leaders sharing real strategies for conquering data complexity and building AI solutions that work. Host Saket Saurabh, CEO of Nexla, delivers practical insights on tackling data variety, moving AI from pilot to production, and making transformation actually happen.</span></p> - How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Information about guest appearances is not available.
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