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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John O'Gorman and I discussed his career as a very early data OG, how he might have created one of the first analytical stores, the fundamentals of semantics, data products, and much more.

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Sarah Floris (aka The Dutch Engineer) is prolific with creating content aimed at DataOps and data engineering. In this wide ranging chat, we cover content platforms for technical creators, podcasting, data engineering vs ML engineering, why DataOps is awesome, courses, layoffs, and much more.

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I've been spending some time in Europe, and most recently returned from Germany the other day. There are definitely some differences between the US and Europe, particularly in how each conducts business and regulation. Tune in for my thoughts on these differences.

data #dataengineering #datascience

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Katharine Jarmul (Principal data scientist at Thoughtworks and author of Practical Data Privacy (O’Reilly, 2023)) and I chat about all things data privacy. She brings battle-tested experience and unique perspectives in the areas of ML/AI privacy, AI risk, regulation, and much more. I learned a ton, and I hope you do too!

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

Twitter: https://twitter.com/kjam

Probably Private newsletter: https://probablyprivate.com/

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The economic downturn is affecting the tech and data industry in a major way. Lots of layoffs, consolidation, and pain. But is this also a good thing for the industry? Listen and get my opinion in this nerdy rant about the economy, interest rates, and doing more with less.

data #dataengineering #datascience

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Neelesh Salian joins the show to discuss the rise of data engineering, where the data landscape is heading, and career growth as an engineer. Neelesh has a ton of experience in the technology space, and you'll learn a lot from his wisdom.

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

Substack: https://hysterical.substack.com/

Twitter: https://twitter.com/neelesh_salian

dataengineering #data #careeradvice #softwareengineering #swe

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I teach data at the University of Utah, and I’m also on the board of advisors for my department. What curriculum and approach do I advise universities use for teaching data and technology? Listen and find out.

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Ken Jee joins the show to chat about how he makes awesome content, podcasting and being authentic, jiu jitsu, maximizing your time, and adapting to AI.

datascience #kenjee #data #ai

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ChatGPT was the iPhone moment for AI, and things are moving insanely quickly. What do generative AI models mean for us, especially children, who are arguably the last of the Pre-AI generation? I dive into some thoughts this week about how we need to work alongside the machines, the impact of generative AI on kids, and so on. Buckle up. We are in for a very interesting next few years as we sort out where AI fits into our day-to-day lives.

data #datascience #dataengineering #chatgpt #ai

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Ryan Dolley and I chat about why BI needs to evolve, moving beyond dashboards, the impact of generative AI on analytics, SuperDataBros, and more.

data #analytics #businessintelligence #datascience

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Is data modeling on life support? I posed this question to LinkedIn earlier this week. It got a fair number of replies, some supportive and others saying I'm full of sh*t. In this 5 minute Friday nerdy rant, I unpack what I mean by data modeling being on life support, and where I think data modeling needs to go given newer practices like streaming and machine learning, which aren't currently discussed in data modeling circles.

LinkedIn post about data modeling on life support: https://www.linkedin.com/posts/josephreis_dataengineering-datamodeling-data-activity-7048722463010013185-OyIy

dataengineering #datamodel #data

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Shane Gibson joins the show to discuss how to make data modeling more accessible, why the world's moved past traditional data modeling, enabling data mesh, and more.

Shane's LinkedIn: https://www.linkedin.com/in/shagility/

Shagility: https://shagility.nz/

Shane's podcasts: https://shagility.nz/podcasts/

If you like this show, give it a 5-star rating on your favorite podcast platform.

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