This week on The Data Stack Show, John is joined by the Cynical Data Guy (Matt Kelliher-Gibson) as they look back on Christmas and New Year’s as they delve into the evolving data landscape. They discuss trends in AI, the year-end rush for product releases dubbed “12 days of shipments,” and the dynamics between data engineers and analysts. The conversation also highlights the importance of data warehousing and open-source data formats, reflecting on the industry’s shift towards more accessible and flexible data practices. The episode concludes with reflections on 2024 and hopes for continued progress in data management in this new year. Don’t miss it!

This week on The Data Stack Show, John is joined by the Cynical Data Guy (Matt Kelliher-Gibson) as the pair welcomes back Joe Reis to the show. Joe discusses his new book on data modeling and shares insights on the evolution of data modeling practices, emphasizing the need to understand various data types and use cases. The conversation explores challenges in data education, highlighting the limitations of traditional academic programs and the importance of foundational principles over specific tools. The group also delves into hiring practices, stressing the value of character and continuous learning. The episode concludes with reflections on the impact of AI, the future of data education, and more.

This week on The Data Stack Show, Eric and John welcome back to the podcast Sokratis Vidros, VP of Engineering at Novu. Sokratis shares his journey in the tech industry, focusing on startups and software engineering best practices. He emphasizes the importance of team dynamics, balancing creativity with stability, and effective communication in early-stage companies. The group discusses the challenges of building software, the significance of version control, and leveraging AI tools in modern data workflows. The conversation also covers hiring strategies, managing stakeholder expectations, fostering a culture of experimentation, valuable insights for those navigating the complexities of startups and data engineering, and so much more.