The Joe Reis Show

Discover the speaker's journey in creating an online data engineering course. Explore the nuanced differences between writing books and developing courses. Learn why producing high-quality content is crucial in our AI-driven world. Get insights on making content timeless and relevant in a rapidly changing tech landscape.

Chris Bergh, an expert in DataOps and founder of DataKitchen, dives deep into the complexities of data processes. He emphasizes the importance of lean principles to reduce waste and improve team efficiency. The conversation highlights the need for effective user engagement and the iterative nature of product development. Bergh also addresses the challenges of managing technical debt and evolving Agile methodologies within data teams. He advocates for cultural shifts in traditional enterprises to foster innovation, community, and collaboration in the data landscape.

In a lively discussion from Berlin, the focus is on the timeless need for quality in software development. The importance of 'slack time' is highlighted as a crucial factor for creativity and combating burnout. The conversation also tackles the challenges organizations face in adopting new technologies, with innovation labs emerging as a solution. As AI evolves, there's debate on whether it will improve quality or just spark faster productivity. Exciting upcoming events in the tech space are also on the horizon!

Lexi Pasi, a PhD in logic known for her unique approach to AI and data science, delves into the fascinating world of symbolic logic in AI. She highlights the evolution of machine learning, contrasting traditional methods with modern deep learning. Lexi discusses the philosophical implications of infinity and foundational assumptions in data science. The importance of mentorship and collaboration in data science is emphasized, along with the interplay between mathematical foundations and real-world applications. Exciting insights into AI’s future are also explored.

The host discusses speaking up on industry issues, emphasizing the importance of expressing controversial thoughts. They critique the value of honest products over superficial AI technology and highlight the necessity of technical understanding in leadership roles.

Data engineering expert and educator Joseph Machado shares insights on creating quality content, balancing technical details, and simplifying complex technical topics in the data industry. He discusses the evolution of educational resources and the challenges faced by data teams in gaining recognition.

Reflecting on cyber vulnerability and practitioner connections, the podcast dives into the importance of assessing single points of failure and fostering vendor-free spaces. It also highlights the value of data therapy sessions for data teams to address challenges and promote open conversations.

Paco Nathan, an AI expert since the 1980s, discusses early chatbots, nostalgia of the mid-90s internet, resurgence of symbolic AI, IBM's shift to SQL, and the impact of graphs in various industries. The conversation also touches on inpainting techniques, transition from GNNs to LLMs in machine learning, and the importance of collaboration and domain expertise in AI development.

Shachar Meir, a data expert, talks about the 3 missing ingredients in data. He discusses building trust and communication in data teams, enhancing clarity in communication for data engineers, the importance of data engineers having a seat at the decision-making table, navigating challenges in work and entrepreneurship, and exciting developments in the data industry.

Matthew Mullins joins me to chat about a recent "get off my lawn" post along the lines that a lot of things we're trying to reinvent in data have already been done, and we're generally overcomplicating the hell out of things. I agree with him. In this episode, we rant about a few of the topics in his post. The post: https://www.linkedin.com/feed/update/urn:li:activity:7217116669188485121/