Listener John sent in a classic question: should you build one all-encompassing data model, or should each part of your business have its own? If you think the answer is black and white, well, welcome to the world of data modeling, where nuance reigns supreme.

Rob and Justin dive deep into the pros, cons, and inevitable mistakes of both approaches. Along the way, they call out the biggest modeling traps, expose the myths that make projects stall, and introduce a revolutionary new acronym: JGS (Just Get Started). Because, spoiler alert, the best data model is the one that actually gets built.

This is an episode you won’t want to miss!

Ever find yourself overthinking a problem until you’ve thought yourself right into a corner? Yeah, we’ve been there too. But what if there was a way to cut through the noise and just know when something is a good idea? Enter Miller’s Theorem, a simple but sneaky-effective thought experiment that’s been kicking around in our conversations for years. It’s the kind of thing that sounds like nonsense at first until it doesn’t.

In this episode, we unpack how a casual visit to a bougie home décor store in Seattle turned into an existential crisis over tariffs, pricing psychology, and whether customers actually care if their overpriced alpaca throw just got 25% more expensive. But it’s not just about economics. It’s about how we make decisions, avoid self-inflicted complexity, and maybe stop outsmarting ourselves into bad choices.

Also on the table: the contrapositive, the dangers of taking political soundbites at face value, and why abolishing the IRS is an idea so catastrophically bad it might actually make the Great Depression look like a mild inconvenience. It’s a wild ride through logic, business, and just enough existential dread to keep things interesting. Listen now, then hope over to LinkedIn and tell us what you think!

Got a topic you would like to have Rob and Justin cover? Join our Raw Data by P3 Adaptive Steering Committee and let us know!

Also in this episode:

Pokerbots, Adware, and Burning Man, w/ Brad Miller & Kai Hankinson

For years, dashboards have been the go-to for business intelligence. Built with the best intentions, loaded with visuals, and meant to empower decision-makers. But are they actually delivering?

A recent Reddit thread raised a tough question: "Has anyone here moved away from dashboards as their main source of insights?"

It’s not the usual “Dashboards are dead” hype. It’s a real challenge from BI pros who build them. The problem?

• Analysts say dashboards can’t keep up with how they really explore data.
• Executives and business users aren’t using them as intended, leading to more ad hoc requests, not fewer.

The result? Dashboards end up underused, misused, or worse, ignored.

In this episode of Raw Data, Rob and Justin cut through the noise and get to the heart of the issue. Are dashboards the problem, or is it how we’re designing and using them? And more importantly, what’s the right way forward?

Also in this episode:

Reddit discussion

Ever sat in a meeting, watching a decision unfold that makes zero sense—bad for business, bad for employees—while the data that should be guiding the way is ignored? You’re not alone. In this solo episode, Rob Collie takes on a question that’s been circling for years: why aren’t more people with a data-driven mindset in leadership positions?

The answer isn’t as simple as “because they should be.” There are deep-rooted reasons why persuasion often wins over precision and why data folks get stuck in support roles instead of calling the shots. But here’s the thing, change is possible. Whether you’re an analyst looking to break into leadership or a decision-maker wondering how to get the most from your data-savvy team, this episode is for you.

Tune in as Rob unpacks the hidden forces at play, the skills that can help data professionals move up the ladder, and why learning the art of influence might be just as important as mastering the numbers.

What happens when you mix fantasy football, data analytics, and a little bit of chaos? You get a conversation that refuses to follow a straight line—but somehow lands exactly where it needs to. Rob Collie welcomes back fantasy football guru Adam Harstad for his third appearance on Raw Data, alongside first-time guests Heather Zimmer and Molly Ferguson, two self-proclaimed newcomers who are anything but casual. They dive into the unexpected ways fantasy football rewires your brain, from strategic obsession to the unshakable belief that your lucky jersey actually controls the game.

Adam breaks down the numbers behind the game—how expected points added (EPA) became the gold standard of football analytics and why your gut feeling about a "bad matchup" might just be a statistical illusion. Meanwhile, Heather and Molly prove that fantasy football isn’t just a game; it’s a full-blown data-driven lifestyle. Whether it’s crunching Power BI models for next season or convincing family members to clear out during game time, they’ve gone all-in—and they’re not looking back.

But beyond the spreadsheets and the smack talk, this episode is about something bigger: the sheer joy of unexpected obsessions. Whether you’re in it for the data, the competition, or just the chance to prove someone wrong (we see you, Heather), fantasy football is a reminder that the best things in life are the ones you never saw coming.

Also in this episode:

Guide to EPA

Protect the Spots with NO Bulletholes, w/ Adam Harstad

Epistemic Path Dependency, w/ Adam Harstad

What if we told you that, before Power BI, most of the money spent on data projects didn’t go where you thought it did? In this episode, Rob Collie and Justin Mannhardt peel back the layers of inefficiency, miscommunication, and just plain bad luck that have haunted data projects for decades. Spoiler: it’s not all doom and gloom. Some of those old headaches are finally getting the boot, thanks to tools like Power BI and the rise of generative AI.

Rob and Justin take an honest look at how data projects have changed over the years, sharing hard-earned lessons and surprising insights from their time in the trenches. They reflect on the glacial pace of old-school BI, how Power BI changed the game, and why AI might be the next big shift.

If you’ve ever wondered why your pre-Power BI data project cost more than a new car, this episode has the answers (and maybe a little therapy). Listen now for insights, laughs, and a sneak peek at the not-so-distant future of data.

As always, be sure to leave us a review on your favorite platform or share the link with a friend to help new listeners find us.

Rob's Visual Aid

Gil Raviv has spent years shaping how we use data. From his early days at Microsoft, where he played a key role in developing Power Query, to his work refining how dashboards serve their users, Gil’s career is a masterclass in making data tools both practical and powerful.

In this episode, we sit down with Gil to dig into why usage data is the missing ingredient for truly effective BI. He explains how understanding what users do with your dashboards can completely change the way you design and deliver them. We also talk about his journey through the world of business intelligence, the lessons he learned along the way, and why he’s so passionate about building tools that meet people where they are.

Whether you’re a Power BI power user or just starting to think about how data fits into your business, Gil’s insights will get you thinking differently.

The world of data technology moves in fascinating ways, and we're excited to have Microsoft MVPs Ed Hansberry and Kristyna Ferris join Justin to unpack what's really happening. This conversation is all about understanding the technologies that are reshaping how we work and think about data.

Microsoft Fabric has been a hot topic, and for good reason. Is it the breakthrough platform everyone's talking about, or are there nuances that aren't making headlines? Ed and Kristyna bring their hands-on experience to share what they've learned—the moments of excitement, the unexpected challenges, and the real potential they see.

Artificial intelligence continues to be a transformative force. We're not just talking about theoretical possibilities, but how AI is actually changing the way data professionals approach problems. What does this mean for teams, for individual careers, for the way we think about technology?

Tune in to find out!

The world’s moving fast, sometimes too fast. Whether it’s AI taking over ad campaigns, fake LinkedIn profiles popping up, or the healthcare system extracting more than it gives, the threads connecting our modern chaos are all too clear. Misaligned incentives and unchecked technologies are reshaping industries, culture, and even how we trust each other. Progress can be exciting, but it’s also raising some tough questions: Are we losing our humanity in the race to optimize everything?

Take Coca-Cola, the apex predator of branding. This holiday season, they swapped their usual creative mastery for AI-generated ads, and people noticed. The results weren’t just underwhelming; they were unsettling. It’s a perfect example of what happens when we try to replicate the human touch with machines that aren’t there yet. But this isn’t just about Coke. It’s about a broader trend of trading quality for convenience and innovation for cost-cutting—and the ripple effects it has on culture, trust, and livelihoods.

This week, we’re unpacking the tension between innovation and integrity, exploring how businesses, governments, and individuals can find a better balance. From the rise of fake AI personas to headlights designed to cheat brightness tests, we’ll dig into what these examples say about the systems we rely on and what happens when those systems fail us. It’s a wild ride, but one thing’s for sure: the way forward has to be more thoughtful than the path that got us here.