In my newsletter last week, I wrote "Data’s still a mess. Most data initiatives fail. Data teams are seen as a cost center and not getting the support they deserve. Same as it ever was."

Here, I unpack those four sentences. Data teams need to stop stop playing to not lose. Instead, they need to play to win!

Navnit Shukla is a solutions architect with AWS. He joins me to chat about data wrangling and architecting solutions on AWS, writing books, and much more.

Navnit is also in the Coursera Data Engineering Specialization, dropping knowledge on data engineering on AWS. Check it out!

Data Wrangling on AWS: https://www.amazon.com/Data-Wrangling-AWS-organize-analysis/dp/1801810907

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

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.

As I travel this Fall, I'm reminded that most people don't work at fancy tech companies. Most people work at traditional companies with "boring" data and tech stacks. And that's OK. Boring is good.

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!

Venkat Subramaniam is a programmer, author, speaker, and founder of Agile Developer, Inc. I've seen him speak several times, and was always blown away by his passion and technical depth. So, I was excited to have him on the podcast.

We chat about agile development in the real world, learning to do less, and much more. Venkat is extremely wise, and I very much enjoyed our discussion. Enjoy!

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

Twitter: https://x.com/venkat_s

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

If you're working on or trying to break into a career in Data Science or Data Engineering, this one is for you. In this episode, Data Engineering expert and recovering Data Scientist Joe Reis shares some of his best tips and strategies for folks looking to launch or accelerate their data careers. You'll leave with practical and actionable advice that you can use to take your career to the next level.   What You'll Learn: Key differences between Analytics, Data Science, and Data Engineering The top skills and tools to focus on for each of these career paths How rapidly changing technology like AI is impacting the future of data jobs   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   About our guest: Joe Reis is a "recovering data scientist" and the co-founder & CEO of Ternary Data. Joe's newest course Fundamentals of Data Engineering Book Follow Joe on LinkedIn

Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

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..

6:00 pm - Intro & Drinks hosted by Chris Tabb

6:10 pm - Session One - High Performance Data Products

David Richardson, Jon Cooke, Taylor McGrath, Mark van der Heijden

6:30pm - Session Two - High Performance Data Models

Joe Reis 🤓, Keith Belanger, Nick White, Eevamaija Virtanen

6:50pm - Pizza and Drinks 🍕🥤🍷🍻

7:00pm - Session Three - High Performance AI

Alex Chung, Jai Parmar, Sonny Rivera, Addie McNamara

7:20pm - Town Hall Debate

Sponsors: Coalesce, LEIT DATA, Rivery, SqlDBM, ThoughtSpot 

In an era where data drives decision-making and innovation, data engineering stands at the forefront of technological advancement. 

This panel brings together leading experts; Chad Sanderson, Joe Reiss, Sarah Levy and Pushkar Garg to explore the critical challenges and opportunities shaping the field today.

For decades, data modeling has been fragmented by use cases: applications, analytics, and machine learning/AI. This leads to data siloing and “throwing data over the wall.”

With the emergence of AI, streaming data, and “shifting left" are changing data modeling, these siloed approaches are insufficient for the diverse world of data use cases. Today's practitioners must possess an end-to-end understanding of the myriad techniques for modeling data throughout the data lifecycle. This presentation covers "mixed model arts," which advocates converging various data modeling methods and the innovations of new ones.

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