The Joe Reis Show

Michel Tricot (CEO of Airbyte) joins me to chat about the impact of AI on the modern data stack, ETL for AI, the challenges of moving from open source to a paid product, and much more. Airbyte & Pinecone - https://airbyte.com/tutorials/chat-with-your-data-using-openai-pinecone-airbyte-and-langchain Note from Joe - I had audio issues cuz he got a new computer and didn't use the correct mic...

Juan Sequeda and I chat about knowledge graphs (he's an OG in this area), the potential of LLMs on structured datasets, and much more. This is an honest, no-BS chat about the transition from a data-first world to a knowledge-first world. Enjoy! LinkedIn: https://www.linkedin.com/in/juansequeda/ data.world: https://data.world/product/ website: https://www.juansequeda.com/

Nowadays, it seems like lots of people want to become data influencers and content creators. Ravit Jain and I chat about how to build an audience, the power of LinkedIn, and much more. The Ravit Show: https://theravitshow.com/ LinkedIn: https://www.linkedin.com/in/ravitjain/

Boring is back. As technology makes the lives of data engineers easier with respect to solving classical data problems, data engineers can now move to tackle "boring" problems like data contracts, semantics, and higher-level and value-add tasks. This also sets us up to tackle the next generation of data problems, namely integrating ML and AI into every business workflow. Boring is good.

Medical data is a mess. Aaron Neiderhiser and Coco Zuloaga from Tuva Health are here (at my house) to answer why this data is insanely complex, and what can be done to fix it. They take a first-principles approach that you might find interesting.

In my travels and virtual conversations with data teams and practitioners around the world, the same thing keep popping up - data teams feel misunderstood and under-appreciated. If we're going to make progress as an industry, it's time to stop playing defense, and start playing offense.

David Foster just published the 2nd edition of his amazing book, Generative Deep Learning (O'Reilly 2023). We chat about a lot - running a consultancy, all things writing, the impact of AI on kids, why in-person events matter more than ever, and much more. David's LinkedIn: https://www.linkedin.com/in/davidtfoster/ Book (Amazon): https://www.amazon.com/Generative-Deep-Learning-Teaching-Mac...

The massive attention on AI means the data industry has a shot at finally succeeding with the things we've been struggling with for decades - "adding value", data quality and modeling, governance, etc. For AI to work, these things need to properly function. But are we up for the task? And if we can't get it right NOW, when?

Whenever Kevin and I get together, we "nerd snipe" each other. This conversation is no different, and it's a wide-ranging conversation about how the data landscape evolves alongside LLMs, education, startup mentorship, and the possible (looming?) startup mass extinction. Kevin's LinkedIn: https://www.linkedin.com/in/kevinzenghu/ Metaplane: https://metaplane.dev/

Matt Housley hangs out at my house and we chat about Data NIMBYism and gatekeeping. What is that? Listen and find out.

Gordon Wong has led data teams of all sizes, across many well-known companies. I consider him a Yoda in the data field, and this is a glimpse into the monthly chats that Gordon and I have. Unfiltered and uncut. Enjoy. Please note - we had to cut it a bit short, as Gordon had another call at the top of the call. Again, this is literally a look at a normal chat that Gordon and I engage in.

This week I had the opportunity to give two talks to two very different groups. Earlier in the week I spoke with a group of senior and above software engineers and leaders in Utah. Yesterday I spoke with a group of data engineers and leaders in Atlanta. The common theme? There's a big divide between dev and data, and data's often on the losing side of this divide. For data teams to be more...

Vin and I chat about the challenges of writing books, how companies can mature with data science, why data scientists need to learn strategy, and much more. (We experienced a slight internet delay around the 15:30 mark, otherwise great) LinkedIn: https://www.linkedin.com/in/vineetvashishta/ Book: https://www.amazon.com/Data-Profit-Businesses-Leverage-Bottom/dp/1394196210 Site: https://www.datascie...

We live in the golden age of data tools, yet we still lack a grasp on the basics of working with data itself - data literacy, modeling, solving problems people care about, etc. It's time to get back to basics, which I think will make data professionals way more effective at their jobs.

Scott Taylor (aka the Data Whisperer) is an OG in data content, speaking, and storytelling. He's been keynoting data events since the 1990s and keeps sharpening his game. Scott is someone I look up to, and I always enjoy our chats. LinkedIn: https://www.linkedin.com/in/scottmztaylor/ Website: https://www.metametaconsulting.com/ YouTube: https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw...

While on a hike today with a friend, we were engrossed in a chat about something that is often overlooked by technical practitioners - the politics of data. This takes many shapes and forms, and ultimately impacts the type of work you do. The main takeaway - learn to pay attention to the broader political landscape of your company.

Kai Zenner has been working on the EI AI Act for a while, and we chat about his perspective on its evolution, challenges, and potential. Along the way, we discuss why the EU AI Act differs from GDPR, why regulating a quasi-global piece of legislation is very difficult, and much more. I admit, politics and regulation are way outside my wheelhouse, and I learned a ton in this discussion. Given the i...

Ryan Boyd and I chat about the evolution and future of databases, the pendulum between single-server and distributed computing, DuckDB and Motherduck, and much more. We also talk about developer relations, which I consider Ryan as one of the OG's in the field. Note - this was recorded the week of Databricks Summit 2023. ----------------------- If you like this show, give it a 5-star rating on...

Is Kimball still relevant? Or should we just throw columnar storage and unlimited compute to solve our analytical needs? Because I like to live on the edge, I respond to a comment online that I think highlights the rot in our industry as it relates to how we view data modeling today. Data Modeling With Joe Reis - Understanding What Data Modeling Is And Where It's Going (Seattle Data Guy): http...

Joshua Bowles is a linguist and data scientist turned software engineer. This is a wide-ranging chat between two old-school data scientists/ML practitioners about the past, present, and future of ML and AI. LinkedIn: https://www.linkedin.com/in/joshua-bowles-ailgroup/ Mastadon: https://infosec.exchange/explore ----------------------- If you like this show, give it a 5-star rating on your favorite...

Benny and I chat about whether data is a profession (in the traditional sense), moving from CDO at a large company to solo consulting, building an audience and staying consistent with content, and much more. LinkedIn: https://www.linkedin.com/in/bennybenford/ Elevating Data to a Profession (link): https://www.datent.com/p/elevating-data-to-a-profession-why Blog: https://www.datent.com ------------...

Imagine two extremes. On one end, data modeling is done perfectly and harmoniously across the data lifecycle. On the other end, data modeling is ignored and thrown into the dustbin of history. Along this spectrum, where do you think we are as a data industry? I'm leaving this question open-ended right for now and would appreciate your thoughts. ----------------------- If you like this show, gi...

Ranjith Raghunath is a customer experience (CX) wizard, and we chat about why CX is important, modeling the customer journey process, the impact of AI on CX, and much more. Ranjith's LinkedIn: https://www.linkedin.com/in/ranjith-raghunath/ CX Data Labs: https://www.cxdatalabs.com/ Note - there were some technical difficulties around the 44:00 minute mark. Nothing major though.

Peter Hanssens is the founder of DataEngBytes, the forward-thinking conference on all things data engineering. In this chat, we talk about what to expect at the 2023 edition of DataEngBytes, the tech scene in Australia, his views on the current and future field of data engineering, and much more. #data #dataengineering #dataengbytes

It's no secret that AI is useful, but it's super hard to cut through the BS. Maya Mikhailov and I chat about the very confusing ML/AI landscape. This is a great discussion that offers many pointers if you want to leverage ML and AI, but you're unsure how to do so. Maya's LinkedIn: https://www.linkedin.com/in/mayam/ Savvi AI: https://www.savviai.com/ #ai #ml #data #datascience