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

I'm starting to see more and more discussions about soft skills and people skills. In this episode, I talk about why tech skills are table stakes, and soft skills are where you need to level up if you want to boost your career.

Office Space clip: https://www.youtube.com/watch?v=hNuu9CpdjIo

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Tristan Handy and I chat about balancing competing tensions, both personally and leading dbt Labs. We also discuss the power of organizational behavior, naming problems to solve, and home remodeling.

This is different from the normal interviews you'll hear with Tristan, and I hope you enjoy it!

dbtlabs #data #analyticsengineering

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After a whirlwind of conferences with the two "big players in the data space," I share some thoughts on how we can improve the conferences targeted at the data engineering community.

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Solomon Kahn has led data teams at startups and big companies. We talk about the advantages of being a data person in a big company, what makes a good data team, why he thinks embedded analytics suck, his new startup Delivery Layer, and much more.

Delivery Layer: https://www.deliverylayer.com/

Solomon's LinkedIn: https://www.linkedin.com/in/solomonkahn/

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Whenever Kris and I chat, there's an agenda, which is totally useless. Every single time we've talked, the conversation goes into different (I'll argue better) directions. In this episode, Kris and I delve into the art and craft of programming, finding your tribe as a developer advocate, and so much more. I hope you enjoy this great and meandering conversation.

Developer Voices podcast: https://open.spotify.com/show/2gXhwz0AQRv2cvw61kobE5

Kris's LinkedIn: https://www.linkedin.com/in/krisjenkins/

Kris's Twitter: https://twitter.com/krisajenkins

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Colleen Fotsch is one of the highest performing (and kindest/nicest) people I know. She's a former NCAA swimmer at UC Berkley, where she was a two-time national champ, American record holder, and Olympic qualifier. She's also a multiple-time Crossfit games athlete and competed on the US National Bobsled Team, where she was supposed to go to Olympic qualifiers, but got sidelined by a tragic injury which she discusses.

On top of all of this, she's a data analyst! In this show, we discuss her evolution from athlete to analyst, the gory details of being a top-level competitive athlete, and much more. If you're interested in what it takes to compete at the highest levels, you'll definitely like this episode.

I'm proud to call Colleen my coach, and I'm also fortunate to mentor her in her data journey. Enjoy!

Instagram: https://www.instagram.com/colleenfotsch/?hl=en YouTube: https://www.youtube.com/c/ColleenFotsch LinkedIn: https://www.linkedin.com/in/colleenfotsch/

I've spoken earlier about why I think data modeling is on life support, and if not dead, definitely a zombie. In this rant, I explore how we got here, the consequences, and what we can do to resurrect data modeling.

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Veronika Durgin joins me to chat about learning and adapting in a fast-changing world, handling vendors, and much more.

Veronika's LinkedIn: https://www.linkedin.com/in/vdurgin/

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Paul Blankley and Ryan Janssen are the co-founders of Zenlytic. They started a BI company with an LLM-first approach (back before LLM's were insanely cool). We talk about the future of BI, and how LLM's will change the face of data and analytics.

Zenlytic: https://www.zenlytic.com/

Paul's LinkedIn: https://www.linkedin.com/in/paulblankley/

Ryan's LinkedIn: https://www.linkedin.com/in/janssenryan/

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Karl "Ivo" Sokolov and I are good friends, and we chat about how he views innovation in Europe, regulations, Western and Eastern Europe, moving from services to a product, and much more. Ivo is a straight shooter, and I always enjoy chatting with him. Enjoy!

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The word "model" is used a lot by data professionals. There are dbt models, machine learning models, relational models, and conceptual, logical, and physical models. My concern is we're missing the bigger picture of what data modeling was initially supposed to accomplish, which was to represent reality and structure it as data. The bigger implication is that our various "models" will become too myopic and miss the larger broader context of the reality of how we use data to serve our organizations.

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George Park is a Czechia-based data engineer. We chat about automation, change management and culture, data modeling (Data Vault in particular), and much more. George lives on the front lines of helping customers, so this is a good discussion if you like to hear from a real practitioner.

George's LinkedIn: https://www.linkedin.com/in/george-park-599846136/

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There's a rush from many countries to regulate AI. Murielle Popa-Fabre is an NLP and ML expert currently working for the Council of Europe, building an international Framework Convention on AI that will touch a wider number of countries (46) than the EU AI Act (only for EU countries). We chat about her path from academia to working in regulation, and the upcoming EU, the Council of Europe, and G7 regulations on AI. These regulations will have a historical impact on what happens next with AI, and it will be very interesting to see where things go from here.

Murielle's LinkedIn: https://www.linkedin.com/in/murielle-popa-fabre-b563187b/

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Rebecca Taylor has a ton of experience with ML, having worked as lead, and senior ML engineer, and holds a PhD in Bayesian Inference. We chat about making ML succeed in larger companies. This is a skill in itself, often requiring stakeholder management and getting buy-in. If you're in a similar situation, this episode is for you!

Rebecca's LinkedIn: https://www.linkedin.com/in/rebecca-taylor-ml-ai/

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Today was pretty cool. My son just finished 6th grade, so proud parent moment. Last week, I spoke to his class about AI. It was a very fun experience and the class was extremely curious about what AI is and how it might impact their lives. In this episode, I discuss some of the things I talked about. I think the lessons apply equally well to adults.

John Kutay and I chat about podcasting and being influencers, a deep dive into change data capture (CDC), Zero ETL, data sharing, Data Mesh, being a vendor in a crowded market, music and art, and more. John is very eclectic, and always a joy to learn from.

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

Twitter: https://twitter.com/JohnKutay

Soundcloud: https://soundcloud.com/jkxo

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In most companies, there's a division between software and data. This needs to end. How to get there?

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John Giles is a legend in the data modeling world, having authored "Nimble Elephant" and "The Elephant in the Fridge," and written extensively on the topic. John and I discuss the power of using data model patterns, enterprise data modeling, "data town plans," and much more. It was an honor to chat with John, and I felt like I was conversing with someone who comes from a more advanced dimension than most data practitioners. You'll learn a ton from this discussion.

John's website: https://www.countrye.com.au/

Books: Nimble Elephant (https://www.amazon.com/Nimble-Elephant-Delivery-Pattern-based-Approach/dp/1935504258), The Elephant in the Fridge (https://www.amazon.com/Elephant-Fridge-Success-Building-Business-Centered/dp/1634624890)

LinkedIn: https://www.linkedin.com/in/john-giles-data/

data #datamodeling

Brian Greene and I chat about how software and data engineering interact, the team dynamics of a startup, and much more. Brian is a no-BS straight shooter, and you'll learn a ton in this discussion.

Brian's LinkedIn: https://www.linkedin.com/in/theotherbriangreene/

Neuronphere: https://www.neuronsphere.io/

data #dataengineering #neutronsphere

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A question I'm asked several times a week is how to learn in a rapidly changing world. To me, this boils down to identifying your true north and mastering the fundamentals. Learn more about my approach in this 5-minute Friday.

If you like this show, give it a 5-star rating on your favorite podcast platform. Purchase Fundamentals of Data Engineering at your favorite bookseller. Subscribe to my Substack: https://joereis.substack.com/

Aaron Wilkerson and I chat about data strategy and leadership, business value and alignment, and the eternal question in our industry - why do data leaders struggle so hard?

Aaron's LinkedIn: https://www.linkedin.com/in/aaron-wilkerson-81bb21a/

datastrategy #data #leadership

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Data products are a very popular topic these days. The challenge is we need new thinking and approaches that differ from how we've worked with data in the past. Jon Cooke and I chat about the mindset shift needed to make data products successful.

Jon Cooke's LinkedIn: https://www.linkedin.com/in/jon-cooke-096bb0/

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I recap the Joe Reis + dbt roadshow in Denver (thanks to everyone who showed up) and discuss the divide between IT and "The Business."

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