Bethany Lyons and I chat about disrupting the recruitment industry, startups, and the future of work.

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.

Ergest Xheblati is a data architect and author of Minimum Viable SQL Patterns. We chat about the opportunities and challenges of SQL, things that don't change in tech and data, writing and publishing books, and much more.

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

Other links: https://www.ergestx.com/links/

Dylan Anderson is a UK-based data strategist. We chat about bridging the gap between data and strategy, why talking about business value is a waste of time, and much more.

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

Substack: https://thedataecosystem.substack.com/

While speaking to one of my best friends, who's worked as a pilot for over 30 years, he mentioned that a "good" pilot doesn't crash the plane. In tech and data, "good" is viewed differently. How good you have to be at your job?

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/

"Do you and Zach Wilson hate each other?"

I get asked questions like this, and it makes me laugh. We're good friends for the record. Most people play zero sum games, where one person wins and another loses. Questions like this got me thinking about how content creation is a positive sum game. You can consume content from many people, and this benefits everyone. Here, I unpack the differences of zero sum and positive sum games.

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/

Most people approach their careers via 1:1 - 1 employee: 1 employer, 1 consultant: 1 client, etc.

In this rant, I discuss why you should consider 1:many as a way to level up your career and visibility.

Christian Steinart and I chat about data consulting in unsexy and niche industries (like roofing in Christian's case). We go through starting a consultancy, the mental game of running a business, getting leads, and much more.

LinkedIn: https://www.linkedin.com/in/christiansteinert96/

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

Chris Bergh joins me to chat about all things DataOps. We also discuss lean, removing waste from data processes and teams, and much more.

DataKitchen: https://datakitchen.io/

DataOps Manifesto: https://dataopsmanifesto.org/en/

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.

Joseph Machado and I chat about teaching data engineering, trends in data engineering, and the state of data content and influencers.

LinkedIn: https://www.linkedin.com/in/josephmachado1991/

Website: https://www.startdataengineering.com/

Data can be a rough industry. Data professionals often feel alone and in need of someone to talk to. I've been hosting "data therapy" sessions for the last couple months. Here are my thoughts on them, and why I think they're critical to helping professionals feel heard and learn from others.

Join here: https://practicaldatamodeling.substack.com/

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/

Shachar Meir joins me for a chat about the three missing ingredients in data, going out on your own, the state of the data industry, and much more.

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

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/