It’s a special edition of The Data Stack Show as we come to you from the Data Council in Austin, Texas. Brooks and Matthew co-host the show to bring you some bonus episodes from some of the leading voices in the data space. This episode, Tristan Zajonc returns to the podcast to discuss the evolution of AI and its integration into applications. Tristan is the Co-Founder and CEO of Continual. In this discussion, the group covers the shift towards generative AI in data science, the progression of machine learning in production, Continual AI copilot platform and the importance of reliability and low latency in AI responses. The conversation also touches on the challenges and future potential of AI copilots in complex industries and large enterprises, considering regulatory and technological breakthroughs needed for widespread adoption, and more. 

It’s a special edition of The Data Stack Show as we come to you from the Data Council in Austin, Texas. Brooks and Matthew co-host the show to bring you some bonus episodes from some of the leading voices in the data space. This episode, Ryan Dolley, Vice President of Product Strategy at GoodData joins the show. During the conversation, Ryan shares his journey from creative arts to data, emphasizing the importance of understanding human behavior in both fields. The discussion also covers his diverse experiences in the data industry, the existential question of what to do with abundant data, the industry’s hype cycles, the challenges of self-serve data projects, the need for a balance between autonomy and governance in analytics, and more. 

This week on The Data Stack Show, Eric and Kostas chat with Ryan Blue, the Co-Founder and CEO of Tabular, and also creator of Iceberg and former Cloudera and Netflix employee. During the episode, Ryan discusses the challenges of managing large-scale data and the development of Iceberg, a new table format. He explains Iceberg’s benefits, such as automatic partitioning and improved metadata management, which simplify data engineers’ tasks and enhance query performance. The conversation covers the importance of atomicity in analytics systems, the scalability of Iceberg, and the trade-offs in mixed workload environments. Additionally, Ryan addresses the differences in cloud object storage performance and the integration of security and access controls into distributed file systems. He also touches on recent Iceberg updates, including Python and Rust support, the anticipation of view support in the upcoming release, and more. 

This week on The Data Stack Show, Eric and Kostas chat with Apurva Mehta, Co-Founder and CEO of Responsive, about event-driven applications and the necessary infrastructure. Apruva shares his journey from LinkedIn to Confluent and eventually founding Responsive, focusing on managing event-driven applications in the cloud. The discussion covers the definition of event-driven applications, the significance of latency and state in event processing, and the evolution of Kafka and Kafka Streams. They also explore the challenges of managing Kafka in production, the developer experience with Kafka Streams, and the operational complexities of running distributed stateful applications. Apruva highlights Responsive’s approach to simplifying the management of these applications, the potential for innovation in event-driven architectures, and more. 

This week on The Data Stack Show, Eric and Kostas chat with Chad Sanderson, the CEO at Gable.ai. During the episode, Chad discusses the complexities of managing the data supply chain, emphasizing the importance of data quality, feedback loops, and aligning incentives within organizations. He shares his journey from analyst to data infrastructure leader at companies like Oracle, Sephora, and Microsoft. Chad introduces his company, Gable, which tackles upstream data quality issues. He critiques traditional data catalogs and advocates for a more dynamic, decentralized approach. The conversation explores the role of metadata, the integration of data quality checks in the software development lifecycle, the need for cultural shifts towards data responsibility, the significance of full lineage graphs and semantic metadata, treating data as a product with quality gates, and more.

This week on The Data Stack Show, Eric and Kostas chat with Kevin Liu, Software Engineer at Stripe. During the episode, Kevin discusses data infrastructure challenges and the development of data products. He also shares insights on the importance of metadata management and the role of catalogs in maintaining data consistency across various systems. The conversation also covers open-source projects like the Python Iceberg library and the future of databases in the cloud, the ease of use of internal tools, the integration of data for builders, the balance between simplicity and functionality in user interfaces, and more.

This week on The Data Stack Show, Eric and Kostas chat with Mike Driscoll, the CEO of Rill Data. During the episode, Mike recounts his journey from the Human Genome Project to developing the Druid engine, which was created to handle massive advertising data. He discusses Druid’s adoption by major companies and its evolution, emphasizing the importance of speed, simplicity, and scalability in data tools. The dialogue covers the progression of BI tools, the role of object stores, and the integration of AI in data technology. Mike also touches on the significance of SQL and AI’s influence on data visualization, what he would do if he wasn’t working in data, and more.

This week on The Data Stack Show, Eric and Kostas chat with Kunal Agarwal, the Co-Founder and CEO of Unravel Data. During the episode, Kunal discusses the evolution of data operations and the role of Unravel in simplifying these processes. The group discusses the shift towards real-time workloads, the impact of AI and machine learning, and the challenges of cloud migration and managing complex data environments. Kunal shares his journey from fashion to data management and emphasizes the importance of observability for data ops teams. The conversation also covers cost optimization, the productivity of data teams, reliability of data systems, the unique cost management considerations in cloud versus on-premises setups, and more. 

This week on The Data Stack Show, Eric and Kostas chat with Tony Wang, Graduate Research Assistant (PhD) at Stanford University. During the episode, Tony discusses his journey from China to studying electrical and hardware engineering at MIT, his transition to data processing systems for his Ph.D., and the academic-industry connection. Tony shares insights on cloud data processing, the limitations of academic hardware projects compared to industry giants like NVIDIA, and the potential for software innovation in academia. He also delves into his current research focus on time series data management, the challenges of integrating different data systems, the goal of improving data processing efficiency, the sales aspect of his research, and more. 

This week on The Data Stack Show, Eric and Kostas chat with Peter Chapman, Peter is a consultant who specializes in helping PLG companies drive more revenue with data. With a background in data and revenue operations, Peter shares his experiences in building data stacks at startups like Heroku, emphasizing the early consideration of data architecture to avoid future issues. He highlights the significance of a cohesive data stack for product-led growth companies and the unique challenges faced by open-source companies in commercializing their projects. The conversation also explores the operationalization of data, the importance of aligning sales with a company’s technical ethos, debating the balance between inference and training costs, the strategic approach to margins by focusing on enterprise features over infrastructure reselling, and more. If you’d like to contact Peter about his advisory services, his email is peter@chapman-coaching.com.