The Analytics Power Hour
Technology
About
Attend any conference for any topic and you will hear people saying after that the best and most informative discussions happened in the bar after the show. Read any business magazine and you will find an article saying something along the lines of "Business Analytics is the hottest job category out there, and there is a significant lack of people, process and best practice." In this case the conference was eMetrics, the bar was….multiple, and the attendees were Michael Helbling, Tim Wilson and Jim Cain (Co-Host Emeritus). After a few pints and a few hours of discussion about the cutting edge of digital analytics, they realized they might have something to contribute back to the community. This podcast is one of those contributions. Each episode is a closed topic and an open forum - the goal is for listeners to enjoy listening to Michael, Tim, and Moe share their thoughts and experiences and hopefully take away something to try at work the next day. We hope you enjoy listening to the
Episodes
- #297: Durable Wisdom in an Age of AI Slop
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 that matters more than ever in an age…
- #296: Avoiding Major Oopsies: Twyman's Law, Intuition, and Valuing Accuracy Over Precision
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 relationship can either build or destroy…
- #295: Research and Analytics: the Peanut Butter and Chocolate of Data?
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 these two disciplines with Stefanie Zamm…
- #294: Adapting an Analytics Team to an AI World
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 effective ways to productively drive health…
- #293: Tool Selection and the Unhelpfulness of Feature Comparisons
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 Google Analytics Alternatives , (also av…
- #292: AI Without Adult Supervision with Aubrey Blanche
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 this year's International Women's Day ep…
- #291: The Data Work that Lives in the Shadows
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. It's writing (or vibe-writing?) SQL or…
- #290: Always Be Learning
From a professional development perspective, you should always be learning: listening to podcasts, reading books, connecting with internal colleagues, following useful people on Medium and LinkedIn, and so on. Did we mention listening to p…
- #289: The Imperative of Developing Business Acumen
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 fill all of our time handling as much o…
- #288: Our LLM Suggested We Chat about MCP. Kinda' Meta, No?
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 that we see a lot of online flexing throug…
- #287: 2025 Year in Review
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 special someone for this episode as we collec…
- #286: Metrics Layers. Data Dictionaries. Maybe It's All Semantic (Layers)? With Cindi Howson
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 possibly understand, there's been a need for…
- #285: Our Prior Is That Many Analysts Are Confounded by Bayesian Statistics
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 demystify the world of Bayesian statistic…
- #284: I Used to Think...But Not Any More
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 beliefs they had at one time that they n…
- #283: Good Things (Can) Come in Small Datasets with Joe Domaleski
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 have limited web traffic, small email li…
- #282: Using (and Creating!) Data to Understand Pop Culture with Chris Dalla Riva
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 exercise, and then, over time, that simpl…
- #281: Analytics: The View from the Corner Office with Anna Lee
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 leadership and what great looks like i…
- #280: Dashboards Must Die! Long Live Dashboards! with Andy Cotgreave
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 fired up than to raise the topic of dashbo…
- #279: The Process(es) of Analytics (We Have Thoughts)
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 and consistent manner. On the other ha…
- #278: Is AI Good at Data Analysis? That's the Wrong Question? with Juliana Jackson
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 corner, or is it years away? Or is that…
- #277: ANOVA? I Hardly Know Ya'! with Chelsea Parlett-Pelleriti
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-Pelleriti , made early and often on thi…
- #276: BI is Dead! Long Live BI! With Colin Zima
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 is quick, simple, and clear while preven…
- #275: The Modern Data...Job Search with Albert Bellamy
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 wide-ranging discussion about the ins an…
- #274: Real Talk About Synthetic Data with Winston Li
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, synthetic data offers a compelling altern…
- #273: Data Products Are... Assets? Platforms? Warehouses? Infrastructure? Oh, Dear. With Eric Sandosham
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 have a good definition? If any of these q…
- #272: When the Metric is Calculated and Complex with Dan McCarthy
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 customer acquisition cost (CAC) or customer…
- #271: It Might Be Irrational, but Let's Talk Behavioral Science with Dr. Lindsay Juarez
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 something specific. On this episode, behaviora…
- #270: AI and the Analyst. We've Got It All Figured Out.
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 parts. It's pretty impressive how the re…
- #269: The Ins and Outs of Outliers with Brett Kennedy
How is an outlier in the data like obscenity? A case could be made that they're both the sort of thing where we know it when we see it, but that can be awfully tricky to perfectly define and detect. Visualize many data sets, and some of th…
- #268: You Get an Insight! And YOU Get an Insight! with Chris Kocek
Do you cringe at the mere mention of the word, "insights"? What about its fancier cousin, "actionable insights"? We do, too. As a matter of fact, on this episode, we discovered that Moe has developed an uncontrollable reflex: any time she…
- #267: Regression? It Can be Extraordinary! (OLS FTW. IYKYK.) with Chelsea Parlett-Pelleriti
Why? Or… y? What is y? Why, it's mx + b! It's the formula for a line, which is just a hop, a skip, and an error term away from the formula for a linear regression! On the one hand, it couldn't be simpler. On the other hand, it's a broad an…
- #266: AI Projects: From Obstacles to Opportunities
In celebration of International Women's Day, this episode of Analytics Power Hour features an all-female crew discussing the challenges and opportunities in AI projects. Moe Kiss, Julie Hoyer and Val Kroll, dive into this AI topic with gue…
- #265: Connected Wellness in the Age of AI with Michael Tiffany
Every listener of this show is keenly aware that they are enabling the collection of various forms of hyper-specific data. Smartphones are movement and light biometric data collection machines. Many of us augment this data with a smartwatc…
- #264: When the Analyst's Toolbox Includes Assessing the Zeitgeist with Erika Olson
We all know that data doesn't speak for itself, but what happens when multiple instruments of measurement contain flaws or gaps that impede our ability to measure what matters on their own? Turning to our intuition and triangulation of wha…
- #263: Analytics the Right Way
Every so often, one of the co-hosts of this podcast co-authors a book. And by "every so often" we mean "it's happened once so far." Tim, along with (multi-)past guest Dr. Joe Sutherland , just published Analytics the Right Way: A Business…
- (Bonus) 2024 Listener Survey...Wrapped!
The start of a new year is a great time for reflection as well as planning for the year ahead. Join us for this special bonus episode where we talk through some of our favorite learnings and takeaways from our 2024 listener survey and some…
- #262: 2025 Will Be the Year of... with Barr Moses
Every year kicks off with an air of expectation. How much of our Professional Life in 2025 is going to look a lot like 2024? How much will look different, but we have a pretty good idea of what the difference will be? What will surprise us…
- #261: 2024 Year in Review
Ten years ago, on a cold dark night, a podcast was started, 'neath the pale moonlight. There were few there to see (or listen), but they all agreed that the show that was started looked a lot like we. And here we are a decade later with a…
- #260: Once Upon a Data Story with Duncan Clark
Data storytelling is a perpetually hot topic in analytics and data science. It's easy to say, and it feels pretty easy to understand, but it's quite difficult to consistently do well. As our guest, Duncan Clark, co-founder and CEO of Flour…
- #259: Dateline Data
There's data, data everywhere, including in the media! Data often gets collected, analyzed, published in a study, covered by a journalist, and then distilled down to a headline. The opportunities for lost-in-translation (or lost-in-simplif…
- #258: Goals, KPIs, and Targets, Oh My! with Tim Wilson
KPIs? Really? It's 2024. Can't we just ask Claude to generate those for us? We say… no. There are lots and lots of things that AI can take on or streamline, but getting meaningful, outcome-oriented alignment within a set of business partne…
- #257: Analyst Use Cases for Generative AI
udging by the number of inbound pitches we get from PR firms, AI is absolutely going to replace most of the work of the analyst some time in the next few weeks. It's just a matter of time until some startup gets enough market traction to m…
- #256: Live at MeasureCamp Chicago
For the first time since they've been a party of five, all of the Analytics Power Hour co-hosts assembled in the same location. That location? The Windy City. The occasion? Chicago's first ever MeasureCamp! The crew was busy throughout the…
- #255: Dear APH-y: Career Inflection Points
To data analyst, or to data science? To individually contribute, or to manage the individual contributions of others? To mid-career pivot into analytics, or to… oh, hell yes! That last one isn't really a choice, is it? At least, not for li…
- #254: Is Your Use of Benchmarks Above Average? with Eric Sandosham
It's human nature to want to compare yourself or your organization against your competition, but how valuable are benchmarks to your business strategy? Benchmarks can be dangerous. You can rarely put your hands on all the background and co…
- #253: Adopting a Just In Time, Just Enough Data Mindset with Matt Gershoff
While we don't often call it out explicitly, the driving force behind much of what and how much data we collect is driven by a "just in case" mentality: we don't know exactly HOW that next piece of data will be put to use, but we better co…
- #252: The Ever-Shifting Operating Environment of the Data Professional
Broadly writ, we're all in the business of data work in some form, right? It's almost like we're all swimming around in a big data lake, and our peers are swimming around it, too, and so are our business partners. There might be some HiPPO…
- #251: The Continued Rise of the Analytics Engineer with Dumky de Wilde
We're seeing the title "Analytics Engineer" continue to rise, and it's in large part due to individuals realizing that there's a name for the type of work they've found themselves doing more and more. In today's landscape, there's truly a…
- #250: Real World Data (RWD) Lessons from Healthcare-land with Dr. Lewis Carpenter
A claim: in the world of business analytics, the default/primary source of data is real world data collected through some form of observation or tracking. Occasionally, when the stakes are sufficiently high and we need stronger evidence, w…
- #249: Three Humans and an AI at Marketing Analytics Summit
How good are humans at distinguishing between human-generated thoughts and AI-generated…thoughts? Could doing an extremely unscientific exploration of the question also generate some useful discussion? We decided to dig in and find out wit…