There's a version of this episode where AI replaces the data visualization expert entirely, and there's a version where it's useless without one. Neither is quite right, according to Cole Nussbaumer K...

Before there was BI, there were "decision support systems." Somewhere along the way, we seem to have quietly dropped the "decision support" part and just kept the systems.

Stephen Follows has spent 15 years turning film-industry curiosity into a career — asking questions like how much movies really earn, why poster colors have shifted, and his theory about Sandra Bulloc...

Everyone’s posting their AI projects online like proud pet owners sharing videos of their cat doing something marginally impressive — cute, occasionally clever, sometimes a little cringe. And the Anal...

Twenty years of digital marketing created something of a monster — not a bad one, but a Working As Designed one. Rusty Rahmer joined Michael, Julie, and Val to talk about why the marketing machine run...

Here’s a question analysts almost never ask themselves before walking into a room: why am I actually here? Not “because it’s the weekly meeting” or “because someone asked me to pull the campaign reado...

There's a certain type of person who first encounters Excel and, instead of running in terror, leans in and grins. Rob Collie has spent his career building things for exactly those people

If you've ever poured months into building a semantic layer only to watch it become shelfware the moment the business pivoted, Jacob Matson has some thoughts. And a metaphor. Your data is a jungle—and...

There are roughly a thousand ways to roll out a new analytics platform, a BI tool migration, or an AI initiative to your organization. Most of them don’t really work. Yehonatan Schwarzmer joins us on ...

Picture this: four analytics professionals, one live audience, a bunch of submitted questions, and absolutely no filter when it comes to sharing their real thoughts about AI, stakeholder management, a...

What do colors, soup kitchens, and mountain climbing have in common? They're all part of the mental models that have shaped how we think about analytics, and they're exactly the kind of durable wisdom...

What do diamond ring shopping, Uber pricing psychology, and active user metrics gone wrong have in common? They all highlight our complicated relationship with precision versus accuracy—and how that r...

Research and analytics: are they more like peanut butter and chocolate, or more like oil and water? On this episode, we dig into the surprisingly common (and surprisingly unfortunate) divide between t...

AI is moving fast. But so is life. AI is widely recognized as a must-adopt technology, but how and where are data workers expected to find the time for that?! Organizations are struggling to find effe...

The one rule about the Analytics Power Hour is that we don’t talk about specific tools. But that doesn’t mean we won’t talk about tool SELECTION! Jason Packer recently released the second edition of G...

As Kevin McCallister once taught us: just because the house is still standing doesn’t mean everything’s under control. Everyone’s racing to adopt AI, but has anyone actually read the fine print? For t...

We know what the work of the data practitioner is, right? It’s everything from managing data ingestion to data governance to report development to experimental design to basic and advanced analytics. ...

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That darn data. It’s so complicated and fragmented and gap-filled and noisy that no amount of time is ever enough to truly get to the bottom of all of its complexity. As a result, it’s pretty easy to ...

If there’s one thing that we absolutely knew would be coming along with the increased interest and use of AI, it would be… more acronyms! And, along with the acronyms, we pretty much could predict tha...

It’s the most…won…derful…tiiiiime…of the year! And by that, we mean it’s the time of the year when we sit back, look at each other, and ask, "Where did all the time go?!" We brought back a very specia...

Semantic layers are having something of a moment, but they’re not actually new as a concept. Ever since the first database table was designed with cryptic field names that no business user could possi...

Permutation Test: Visual Explanation

Before you listen to this episode, can you quantify how useful you expect it to be? That’s a prior! And "priors" is a word that gets used a lot in this discussion with Michael Kaminsky as we try to de...

As the world turns, a couple of things happen: 1) we grow and learn, and 2) the world changes. On this episode, inspired by a job interview question, the hosts walked through a range of thoughts and b...

Does size matter? When it comes to datasets, the conventional wisdom seems to be a resounding, "Yes!" But what about small datasets? Small- and mid-sized businesses and nonprofits, especially, often h...

Disease-causing bacteria that have been recently discovered in the teeth of Napoleonic soldiers may have spurred the massive infantry’s demise during its retreat from Russia

Data does not just magically spring into existence. Someone, somewhere, has to decide what data gets created and the rules for its creation. We would claim that this often starts as a pretty simple ex...

From spreadsheets to strategy: what does data look like from the CEO’s chair? For this episode, we sat down with Anna Lee, CEO of Flybuys and former CFO/COO of THE ICONIC, to get her view on data-led ...

Introducing your future national anthem.

If you didn’t have a visceral reaction to the title for this episode, then you are almost certainly not in our target audience. There are few more certain ways to get a room full of analytics folk fir...

What is "process" in analytics? On the one hand, it can be seen as a detailed sequence of minutia by which anything that needs to be repeated in the world of analytics gets carried out in a structured...

Imagine a world where business users simply fire up their analytics AI tool, ask for some insights, and get a clear and accurate response in return. That’s the dream, isn’t it? Is it just around the c...

By Olivia Walch

Did you know that, upon closer inspection, many a statistical test will reveal that "it’s just a linear model" (#IJALM)? That wound up being a key point that our go-to statistician, Chelsea Parlett-Pe...

Priors prevent bad MMM outputs. Here’s why they matter, why they’re hard to set, and how Recast builds them right.

A loose and unaffiliated companion to #measure Slack, perhaps? Honestly... there was next to no thought put into the creation of this Strava group, which perfectly aligns with both the career and ph...

Product managers for BI platforms have it easy. They "just" need to have the dev team build a tool that gives all types of users access to all of the data they should be allowed to see in a way that i...

It’s a process few people genuinely enjoy, but it’s one which we all find ourselves going through periodically in our careers: landing a new job. We grabbed MajorData himself, Albert Bellamy, for a wi...

ALT: a man says i 'm a little skeptical while wearing earrings

Synthetic data: it's a fascinating topic that sounds like science fiction but is rapidly becoming a practical tool in the data landscape. From machine learning applications to safeguarding privacy, sy...

Is it just us, or are data products becoming all the rage? Is Google Trends a data product that could help us answer that question? What actually IS a data product? And does it even matter that we hav...

Among 60 areas asked about in the survey, more than half of Americans rate themselves above average in 17. In 51, Americans are more likely to rate themselves above average than below average.

ALT: a bald man with a beard is saying what

No matter how simple a metric's name makes it sound, the details are often downright devilish. What is a website visit? What is revenue? What is a customer? Go one level deeper with a metric like cust...

Data that tracks what users and customers do is behavioral data. But behavioral science is much more about why humans do things and what sorts of techniques can be employed to nudge them to do somethi...

We finally did it: devoted an entire episode to AI. And, of course, by devoting an episode entirely to AI, we mean we just had GPT-4o generate a script for the entire show, and we just each read our p...