Data professionals Matt Housley, Chris Tabb, and Joe Reis chat about career advice in the evolving data job market. They discuss remote work challenges, important skill sets for data scientists, proactive job search strategies, in-person collaboration, and the importance of self-motivation in data careers. They also explore ways to improve the value of IT and data teams by adopting a sales or marketing mentality, showcasing data capabilities, and emphasizing the importance of certifications.

Amit Prakash (CTO/Co-Founder of Thoughtspot) joins the show to chat about the future of generative AI in data analytics. Thoughtspot has been a leader in searchable analytics, and it will be interesting to get Amit's take on where the field of analytics is heading next.

Max Howell created Homebrew, one of the most popular open-source software (OSS) packages on the planet. He's also the founder of tea.xyz, which is helping incentivize developers to pursue their OSS projects.In this episode, we chat about the realities and future of OSS, how developers can be remunerated for their OSS projects, and much more. Tea: tea.xyz

Aaron Hunsaker joins Matthew Housley and I to chat about data grifters, dealing with vendors, how data people should converse with "the business", and much more. Aaron doesn't hold back.Enjoy this very candid in-person chat.

Hala Nelson, math nerd, professor, and author, discusses her journey from abstract algebra to real-life applications of math. The speakers talk about their motivation to write a book bridging the gap between math and AI. They give advice for pursuing a career in AI and large language models, emphasizing the importance of interdisciplinary education. They also discuss their new book and its practical applications for AI projects. The chapter on bridging the gap between data engineering and data analysis is highlighted. The importance of feedback and reviewers in the book writing process is emphasized. The hosts discuss the beginnings of their podcast and the value of meaningful conversations.

David Yaffe and Johnny Graettinger (both from Estuary) join the show to do a deep dive into streaming data processing. We also cover how to scale change data capture (CDC) and where transformations belong in data pipelines. Estuary: https://estuary.dev/ Gazette: https://gazette.readthedocs.io/en/latest/ Note - Joe's audio was having issues for this episode. Apologies.

Multiple products, versions, platforms, targets technologies, formats, and locales? How do you make sense of the "multiple of multiples" challenge from a technical perspective? The "language of the business" and data in all its structured, semi-structured, and 'unstructured' forms helps drive this home.John O'Gorman has world-class expertise in language, semantics, and tying this together for the business. We hope you learn something new from this episode.

Brian Olsen joins us again to chat about why Apache Iceberg won the table format war. We also finish our chat from last time about Data Mesh. #dataengineering #datalake #datamesh

David Langer joins the show to chat about how programming languages for data science, BI teams have a unique advantage in helping introduce data science into their organizations.

Devin Petersohn (Modin, Ponder) knows a thing or two about dataframes, having done his PhD thesis on them, among other related achievements. We'll talk about all things dataframes, both high level and in the weeds. If you've ever wanted to learn about dataframes, this is the discussion for you.