This week on The Data Stack Show, Eric and Kostas chat with Travis Henry and Hillary Carpio of Snowflake. Travis works as the Director of SDR Operations while Hillary is Head of ABM. During the episode, Travis and Hillary discuss the importance of data in their marketing and sales strategies. They delve into the types of data they use, the challenges of data overload and the importance of a strong partnership between marketing and data teams. They also share their experience of writing a book about their unique approach at Snowflake. The conversation further explores the role of sales and marketing in targeting different personas within an organization, and more.

This week on The Data Stack Show, Eric and Kostas chat with David Yaffe and Johnny Graettinger, Co-Founders of Estuary, a company building the next generation of real-time data integration solutions. During the episode, David and Johnny discuss streaming technology, the challenges of real-time streaming, the importance of low latency and high-scale data processing in the ad tech industry. They delve into the reasons behind building Estuary, its unique approach to decoupling storage and computing, and its focus on real-time updates and scalability. They also touch on the complexities of state management in streaming applications, data mesh, the impact of streaming on data processing and orchestration, and more.

This week on The Data Stack Show, Eric chats with Mark Huang, Co-Founder and Chief Architect at Gradient, a platform that helps companies build custom AI applications by making it easy to fine tune foundational models and deploy them into production. During the episode, Mark discusses the role of Gradient in simplifying the usage and adoption of LLMs by packaging open-source models into a service. Mark highlights the importance of collaboration and data sharing among enterprises for model development, the impact of LLMs on enterprises, the challenges of operationalizing LLMs, the future of AI and its potential, and more.

This week on The Data Stack Show, Eric and Kostas chat with Chang She, the CEO and Co-Founder of Eto Labs. During the episode, Chang discusses LanceDB, the history and success of Pandas, as well as the challenges of working with new technologies in the data industry. Chang shares his journey and the challenges faced in open sourcing Pandas, the need for new data infrastructure optimized for AI and ML, the future of AI and other data avenues, and more. 

This week on The Data Stack Show, Eric and Kostas chat with Santona Tuli, Head of Data at Upsolver, a data pipeline tool that focuses on application developers. During the episode, Santona discusses her background in nuclear physics. The conversation covers topics such as specialized tools in data infrastructure, the challenges of working with data in different environments, and the importance of data as a business differentiator. They also discuss the features and capabilities of UpSolver and the need for quality and observability in data processing, and more.

This week on The Data Stack Show, Eric and Kostas chat with Bob van Luijt, the CEO & Co-Founder at Weaviate. During the episode, Bob discusses the technical and business aspects of vector databases, delving into their differences from other types of databases and the opportunities they present. Bob shares his journey and how his love for music relates to his work in machine learning. The conversation also covers the progression of database complexity and the emergence of databases designed for specific data types, limitations of existing databases for vector processing, the importance of simplicity and user-friendliness in the user experience, generative feedback loops, and more.

This week on The Data Stack Show, Eric and Kostas chat with Nick Schrock, Founder of Dagster Labs. During the episode, Nick discusses his background at Facebook and his involvement in successful open-source technologies like React and GraphQL. Nick explains the mismatch between the complexity and available tools in the data infrastructure space, leading him to start Dagster Labs. The group also talks about the challenges and fragmentation in the data engineering industry, the need for better abstraction layers, the role of orchestrators, comparing it to GraphQL’s role in product engineering, the importance of data orchestration in the future of data infrastructure and engineering, and more.

This week on The Data Stack Show, Eric and Kostas chat with Amr Awadallah, the Founder and CEO of Vectara. During the episode, Amr discusses his extensive experience in the data industry and his new company, Vectara, which focuses on enabling companies to integrate capabilities in their products using large language models (LLMs) with security, reliability, and ease of use. The conversation also covers the advancements in data, computing, and algorithms that have led to emergent behaviors in neural networks, the practical applications of Vectara’s technology, the challenges and considerations in working with large language models, the importance of addressing technology misuse and aligning different value systems in society, and more.

This week on The Data Stack Show, Eric and Kostas chat with Alex Gallego, the Founder & CEO of Redpanda Data. During the episode, the group discusses the importance of Kafka in data infrastructure and the lack of competition in the market. Alex shares his background in streaming systems and the development of Redpanda. The conversation also includes the challenges of operationalizing streaming systems and the evolution of storage systems, using WebAssembly as the interface for writing functions, the key differences between Redpanda and other streaming platforms, where the name Redpanda came from, and more.

This week on The Data Stack Show, Eric and Kostas chat with Pardis Noorzad, the CEO of General Folders. During the episode, Pardis Noorzad shares her journey as a data scientist and entrepreneur in founding a company. The conversation includes the importance of data collaboration and sharing, the challenges and complexities of data sharing in various industries, the need for efficient and secure solutions, the underlying definitions and dimensions of the data exchange problem, including infrastructure, security, economics, and user needs, and more.