This week on The Data Stack Show, AI entrepreneur Alberto Rizzoli shares his journey from early computer vision breakthroughs to leading the automation of back-office workflows at V7. The discussion explores the shift from bespoke model training to configurable AI solutions, the impact of automation on business roles, and emerging best practices for integrating AI into enterprises. Listeners will gain insight into how AI infrastructure is moving from labs to everyday businesses, which roles are most vulnerable or secure amid automation, and why future-proofing your career means focusing on creativity, first principles, and continuous improvement. Don’t miss it!

This week on The Data Stack Show, Ryan Dolley joins Eric and John to discuss his unique journey from playwriting to leading product strategy in the data industry. The conversation explores the evolution of business intelligence (BI), the growing influence of AI on analytics, and the shifting skill sets required for data professionals. Key topics include the challenges of adapting to rapid technological change, the importance of embracing engineering practices in BI, and the need for continuous learning. Listeners will gain insights into how AI is transforming data roles, why storytelling remains central to analytics, practical advice for thriving in a fast-changing industry, and so much more. 

This week on The Data Stack Show, Eric Dodds and John Wessel explore how AI is reshaping the data industry, focusing on the ongoing cycles of bundling and unbundling within data infrastructure. They discuss the potential for closed ecosystems like Notion to deliver personalized, integrated experiences and examine recent industry moves such as Fivetran’s acquisitions. The conversation also highlights the challenges faced by both startups and incumbents, the influence of enterprise customers on product development, and the enduring importance of trade-offs when choosing between bundled and unbundled solutions. Key takeaways include the complexity of implementing AI across platforms, the likelihood that market cycles will persist despite technological advances, and the need for organizations to carefully weigh integration, flexibility, and long-term risk when adopting new data tools.

This week on The Data Stack Show, the crew welcomes Eric Dodds back to the show as they dive into the realities of integrating AI and large language models into data team workflows. Eric, Matt, and John discuss the promise and pitfalls of AI-driven automation, the persistent challenges of working with APIs, and the evolution from big data tools to AI-powered solutions. The conversation also highlights the risks of over-reliance on single experts, the critical importance of documentation and context, and the gap between AI marketing hype and practical implementation. Key takeaways for listeners include the necessity of strong data fundamentals, the hidden costs and risks of AI adoption, the importance of balancing efficiency gains with long-term team resilience, and so much more.

This week on The Data Stack Show, Eric and John welcome back Kostas Pardalis, long-time co-host of the Data Stack Show and now Co-Founder of typedef. The group discusses the rapid evolution of AI and data infrastructure. The conversation also explores how AI is accelerating industry change, the challenges of integrating large language models (LLMs) into data workflows, and the limitations of current semantic layers. Kostas shares insights on building next-generation query engines, the importance of using familiar engineering paradigms, and the need to make AI seamless and almost invisible in user experiences. Key takeaways include the necessity of practical, incremental innovation, the reality behind AI hype, strategies for making advanced data tools accessible and reliable for engineers and businesses alike, and so much more. 

This week on The Data Stack Show, John and Matt dive into the latest trends in AI, discussing the evolution of GPT models, the role of tools in reducing hallucinations, and the ongoing debate between data warehouses and agent-based approaches. They also explore the complexities of risk-taking in data teams, drawing lessons from Nate Silver’s book on risk and sharing real-world analogies from cybersecurity, football, and political campaigns. Key takeaways include the importance of balancing innovation with practical risk management, the need for clear recommendations from data professionals, the value of reading fiction to understand human behavior in data, and so much more. 

This week on The Data Stack Show, John and Matt bring you another edition of the Cynical Data Guy. John and Matt dive into the evolution of customer data infrastructure, the growing influence of low-code tools like Clay, and the blurred lines around the “engineer” title in modern data roles. They also discuss the trade-offs between SaaS adoption and building custom solutions, the pitfalls of enterprise software buying, and the realities of platform lock-in—using Palantir’s unique business model as a case study. Key takeaways include the importance of simplicity and scalability in data engineering, the need for clear requirements when evaluating tools, and a healthy skepticism toward sales pitches and “art of the possible” features. Don’t miss this month’s Cynical Data Guy. 

This week on The Data Stack Show, Brooks and John chat with Andy MacMillan, CEO of Alteryx. Andy discusses the evolving landscape of data and AI, focusing on empowering business users to solve complex problems. He explores the concept of “citizen developers” and how tools like Alteryx can bridge the gap between IT and business teams by democratizing data access. The conversation also emphasizes the importance of creating controlled environments where business users can leverage cloud data platforms and AI technologies to reimagine workflows, without bypassing governance. Key takeaways include the need for organizations to enable innovation through accessible data tools, the potential of AI-driven agents to transform business processes, the critical role of employees who understand their business functions in driving technological transformation, and so much more.

This week on The Data Stack Show, John and Matt bring you another edition of the Cynical Data Guy. John and Matt dive into the quirky world of data analytics, exploring common challenges like unrealistic data requests, the limitations of self-service BI, and the evolving role of data analysts. They also discuss the importance of understanding business context, the need for effective data storytelling, and the emerging trend of “BI as code” which promises more flexible and version-controlled analytics tools. The conversation highlights the gap between technical data capabilities and business user needs, emphasizing that the real value of data professionals lies not just in tool proficiency, but in their ability to provide meaningful insights and guide decision-making. Key takeaways include the importance of context in data analysis, the limitations of self-service tools, the ongoing evolution of data roles in modern organizations, and more.

This week on The Data Stack Show, John chats with Paul Blankley, Founder and CTO of Zenlytic, live from Denver! Paul and John discuss the rapid evolution of AI in business intelligence, highlighting how AI is transforming data analysis and decision-making. Paul also explores the potential of AI as an “employee” that can handle complex analytical tasks, from unstructured data processing to proactive monitoring. Key insights include the increasing capabilities of AI in symbolic tasks like coding, the importance of providing business context to AI models, and the future of BI tools that can flexibly interact with both structured and unstructured data. Paul emphasizes that the next generation of AI tools will move beyond traditional dashboards, offering more intelligent, context-aware insights that can help businesses make more informed decisions. It’s an exciting conversation you won’t want to miss.