The Analytics Engineering Podcast

Yohei Nakajima, investor and coder, discusses the experimental nature of AI agents like BabyAGI, the evolution of AI models like GPT-4, and the potential for AI in managing tasks traditionally handled by humans. He explores the challenges and experimentation involved in task planning for AI agents, the impact of AI-generated spam in emails, and the augmentation of VC work with AI for innovative marketing strategies.

Misha Panko, CEO of Motif Analytics, discusses event stream data, AI models for event sequences, and breakthroughs in language modeling in this episode. They explore the complexities of event data, the challenges of working with event stream data, and how Motif applies AI to train foundation models of event sequences.

Journalist veteran Eric Avidon discusses AI maturity, data quality, and AI strategies of Snowflake and Databricks. They touch on the evolution of analytics stack, generative AI, and vendor consolidation in the data space. Reflecting on aspirations for user-friendly analytics tools with natural language processing.

Barry McCardel, CEO of Hex, discusses notebooks in data analysis, AI hype cycles, building AI products, and AI impact on data practitioners. They explore Hex's collaborative platform, market structure in data tools, evolution of HEX in organizations, job title shifts in data science, practical AI applications, and envisioning data teams' future.

Matt Turck, the publisher of the MAD Landscape map, discusses the 2024 ecosystem with 2,011 logos. Topics include generative AI impact, modern AI vs data stack, Databricks vs Snowflake, and Microsoft's entry into the data landscape.

Journalist/data practitioner Matthew Lynley discusses the rise of Gen AI in the media, his journey from mathematics to journalism, encountering Chat GPT, challenges of monetizing an AI newsletter, AI content creation, and the convergence of fields in AI development.

Topics discussed include semantics, text-to-SQL performance, AI's impact on structured data analytics, evolution of semantic web, knowledge graphs, observability in business analysis, GPT-4 for text to SQL, design patterns in LLM interaction, and knowledge management in the data industry.

Exploring the evolution of the modern data stack, AI integration in analytics, Mode's transformation to a cloud-first company, AI-powered formula builder for SQL queries, redefining the modern data stack, empowering business through IT and data teams, and envisioning the future of the data industry.

Moritz Heimpel from Siemens and Ben Flusberg from Cox Automotive discuss their experiences adopting a data mesh architecture and collaborating with data at scale in large organizations. They explore topics such as setting up infrastructure to scale, domain specific ownership of data, data security, and the future of the data industry.

Brandon Taylor and Michael Olschimke discuss the Data Vault approach, its adoption in Europe, alignment with data mesh architecture, and the ongoing debate over Data Vault vs. Kimball methods. They also explore the impact of DataMesh on data warehouse design, recommended data modeling approaches, and hopes for the data industry.