Valentin Becerra and I chat about DJing, AI, space engineering, and much more.

Multi-tenancy in databases is very difficult to pull off at scale. Gwen Shapira and I chat about multi-tenant databases at Nile (and elsewhere), AI, RAG, and much more.

People often ask me for career advice. In a tough job market where people are sending out thousands of resumes and hearing nothing back, I notice a lot of people have weak networks and are unknown to the companies they're applying to. This results in lots of frustration and disappointment for job seekers.

Is there a better way? Yes. People need to know who you are. Obscurity is your enemy.

Also, the name of the Friday show changed because I can't seem to keep things to five minutes ;)

My works:

📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/

🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering

🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/

🤓 My SubStack: https://joereis.substack.com/

Let's do things the right way, not just the fast way.

My works:

📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/

🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering

🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/

🤓 My SubStack: https://joereis.substack.com/

I speak at a lot of conferences, and I've lost track of how many questions I've answered. Since conferences are top of mind for me right now, here are some tips for asking good (and bad) questions of speakers.

My works:

📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/

🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering

🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/

🤓 My SubStack: https://joereis.substack.com/

I've seen a TON of horror stories with tech debt and code migrations. It's estimated that 15% to 60% of every dollar in IT spend goes toward tech debt (that's a big range, I know). Regardless, most of this tech debt will not be paid down without a radical change in how we do things. Might AI be the Hail Mary we need to pay down tech debt? I don't see why not...

My works:

📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/

🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering

🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/

🤓 My SubStack: https://joereis.substack.com/

Vijay Yadav (Director of Data Science at Merck) joins me to chat about a very interesting project he launched at Merck involving LLMs in production. A big part of this discussion is how to make data ready for generative AI.

This is a great example of an LLM-native use case in production, which are rare right now. Lots to learn from here. Enjoy!

LinkedIn: https://www.linkedin.com/in/vijay-yadav-ds/

I've spent the last three weeks visiting the UK, Australia, and New Zealand. Here are my observations and anecdotes about the data and ML/AI industry from countless chats with executives, practitioners, and pundits.

Ilya Reznik has been in the ML game for ages, having worked at Adobe and Twitter and led teams at Meta, among others.

We chat about leading ML teams, AI today, creating content, and much more.

LinkedIn: https://www.linkedin.com/in/ibreznik/

Jordan Morrow has written a ton, including four books. We chat about the process of writing books, the ins and outs of working with a publisher, the role of AI in writing, and much more. If you're interested in writing a book, this is a crash course in what you should know. Enjoy!

Uncle Rico is a character in the movie Napoleon Dynamite, who is stuck in the past, reminiscing about his days as a high school football star. If only he'd won the game and went to the state championship. Some of the data industry reminds me of Uncle Rico.

During a recent panel, there was a question about whether AI can help with data management (governance, modeling, etc).

Some people were quick to dismiss this, saying that machines are no substitute for humans in their understanding and translating of "the business" to data.

Yet why are we still perpetually stuck in the mode of "80% of data projects fail"? Might AI/ML help data management move out of its rut? Or will it stay stuck in the past?

Also, please check out my new data engineering course on Coursera!

https://www.coursera.org/learn/intro-to-data-engineering

Paco Nathan is a national treasure. He's not only an OG in the field of AI, but he's also instrumental in early hacker and cyberpunk culture.

When I first met Paco, it suddenly clicked that I'd seen his name in various cyberpunk and alternative zines back in the 1990s. We have a chat all sorts of crazy stuff, and I feel like we only got to 5% of the stories..

Last week I talked about how good you have to be at your job. Yesterday's OpenAI announcement of it's "reasoning" model, o1, got me thinking about how good AI needs to be to do our jobs.

Jordan Tigani is back to chat about why small data is awesome, data lakehouses, DuckDB, AI, and much more.

Motherduck: https://motherduck.com/

LinkedIn: https://www.linkedin.com/in/jordantigani/

Twitter: https://twitter.com/jrdntgn?lang=en

Demetrios Brinkmann is the co-founder of the massively global MLOps Community. We chat about AI hype vs reality, building a global tech community, and ROI of AI projects, and much more.

LinkedIn: https://www.linkedin.com/in/dpbrinkm/

MLOps Community: https://mlops.community/

Vinoo Ganesh is an open source enthusiast and contributor, and a data and ML engineer. We chat about strong open source communities, LLMs and AI, and much more.

Lekhana Reddy is a data content creator focusing on mindfulness. We chat about how mindfulness in technology is key, especially given the need to maintain humanity with the rise of AI.

LinkedIn: https://www.linkedin.com/in/lekhanareddy/

Instagram: https://www.instagram.com/storytellingbydata/

Until recently, Nik Suresh wrote under a mysterious blog that had several viral posts, including the famous "I Will F*cking Piledrive You If You Mention AI Again." For the longest time, he was an underground sensation, with nobody (not even his friends) knowing his identity.

In this episode, we chat about his blog posts (I'm a huge fan), the realities of data science and data engineering, and much more. This is a very candid and fun chat where I'm actually the fanboy, so enjoy!

Blog: https://ludic.mataroa.blog/

I've been saying for years, most companies are barely doing BI, let alone AI. Last week, I posted about this on LinkedIn and it went viral. Here, I unpack what I mean by that post.

The post: https://www.linkedin.com/feed/update/urn:li:activity:7230408663125913600

Rehgan Bleile joins me to chat about the challenges and importance of AI governance and adoption. We also discuss the lack of representation of women in conferences, and efforts to create genuine opportunities for women speakers. 
 AlignAI: getalignai.com LinkedIn: https://www.linkedin.com/in/rehganavon/ Women in Analytics: https://www.womeninanalytics.com/

I've been head's down finishing my upcoming Data Engineering course on Coursera, and working on the new book. In this episode, I chat about the differences between courses and books, why high quality content matters more than ever in the age of AI, and much more.

Enroll in the new DeepLearning.AI Data Engineering Professional Certificate course here!

https://www.coursera.org/professional-certificates/data-engineering

Hanging out in Berlin right now. Re-read Peopleware (originally released in 1987), and it got me thinking about what hasn't changed in tech and data. Namely, we tend to rush through things in the name of productivity instead of focusing on quality. Will AI help this? Maybe and maybe not.

Lexi Pasi and I chat about symbolic logic in AI, building and managing data science teams, math, and the shapes of ML/AI problems.

Lexi is one of my favorites to talk to because she's so left-field yet so effectively reasonable and logical (she does have a PhD in logic...).

LinkedIn: https://www.linkedin.com/in/alexandrapasi/

I've been told that I "say the quiet parts out loud." It might be calling out "data science" and AI as overhyped, or anything else I've ranted about online over the years.

In this episode, I unpack what that means and why I do it.

Paco Nathan and I chat about early chatbots, and all things AI, especially since the 1980s. We also riff on how we intersected in the early days of the Internet.

Paco is one of my faves, so expect him back for another interview soon.

X: https://twitter.com/pacoid

LinkedIn: https://www.linkedin.com/in/ceteri/