This week on The Data Stack Show, it’s the next rendition of the Cynical Data Guy. Eric and John are joined by Matthew Kelliher-Gibson, the Cynical Data Guy, for their monthly discussion. They engage in a lightning round, analyzing various LinkedIn posts related to data and data science. Topics include data teams’ transparency with stakeholders, simplifying complex data, generative AI’s role in cultural adoption, and the impact of the “sexiest job of the 21st century” article on data science careers. The group also discusses the influence of “Moneyball” on data science perceptions, the importance of understanding data models, and more.

This week on The Data Stack Show, Eric and John chat with Cameron Jagoe, Co-Founder and CEO of ProcureVue. Cameron discusses his journey from running a bakery, where he used data analytics to tackle profitability issues, to co-founding ProcureVue. He shares insights on optimizing business operations through strategic sourcing and data-driven decision-making. Cameron also highlights his work at Newell Rubbermaid, where he improved profitability through cost-cutting and value engineering. The conversation delves into the technical aspects of ProcureVue, emphasizing its role in driving cost savings and improving procurement processes for businesses, and so much more. 

This week on The Data Stack Show, Eric and John chat with Jesse Clark, the Co-Founder & CTO of Marqo.ai. During the episode, Jesse discusses the evolution of AI and machine learning in enhancing search capabilities, particularly in e-commerce. The group explores the concept of vector search and its advantages over traditional keyword-based methods. The conversation also touches on the challenges of searching for specific items, like car parts for Land Cruisers in Australia, due to the complexity of part numbers and interchangeability. They delve into the difficulties of dealing with unstructured data, such as information locked in PDFs and manuals, and how Marqo is developing AI to search and incorporate this data into relevant results. The episode covers the technical aspects of customizing embedding and language models for better search outcomes and the potential of language models to connect different data modalities for advanced search experiences, the future of interfaces, the role of new technology in search experiences, and more.