Best Digitalanalytics Podcasts (2024)

1
#243: Being Data-Driven: a Statistical Process Control Perspective with Cedric Chin 1:14:20

3d ago1:14:20

1:14:20

It happens occasionally. Someone in the business decides they need to just take the analysis into their own hands. That leaves the analyst conflicted — love the interest and enthusiasm, but cringe at the risk of misuse or misinterpretation. Occasionally (rarely!), though, such a person goes so deep that they come out the other side having internali…

1
#242: The Rise and Fall of Data Communities with Pedram Navid 58:37

17d ago58:37

58:37

Data communities have played a major role in the careers of many analysts, but times they are a-changin'. We're not sure if we're different, if the communities' purposes and missions have shifted, or both. One thing we are confident in, though, is that Pedram Navid was absolutely the right guest to invite on to the show to explore the topic alongsi…

1
(Bonus) Marketing Analytics Summit Is Nigh! 13:08

24d ago13:08

13:08

Long-time listeners to this show know that its origin and inspiration was the lobby bar of analytics conferences—the place where analysts casually gather to unwind after a day of slides interspersed with between-session conversations initiated awkwardly and then ended abruptly when the next session begins. Of the many conferences where this occurs,…

1
#241: The Analyst's Underutilized Tool: the Sketchbook with Dan White 1:05:24

1M ago1:05:24

1:05:24

As a general rule, analysts are drawn to precision: let's understand the business problem and then go figure out how the data can be acquired and crunched to provide something specific and useful. Fair enough. Where, then, do pencil and paper and 10-second sketches fit in? Or hastily and collaboratively drawn flippy chart or whiteboard sketches? We…

1
#240: Asking Better Questions with Taylor Buonocore Guthrie 1:11:56

2M ago1:11:56

1:11:56

They say an analysis is only as good as the question that was asked, so for our 2024 International Women's Day Episode, Julie, Moe, and Val were joined by Taylor Buonocore Guthrie to discuss how to ask better questions. Every analyst is naturally curious, but the thoughtfulness that Taylor puts into what type of questions to ask, how to ask them, a…

1
#239: Non-Technical Backgrounds in the Modern Analytical World with Kirsten Lum 1:02:39

2M ago1:02:39

1:02:39

Is it just us, or does it seem like we're going to need to start plotting the pace of change in the world of analytics on a logarithmic scale? The evolution of the space is exciting, but it can also be a bit dizzying. And intimidating! There's so much to learn, and there are only so many hours in a day! Why did we choose that [insert totally unrela…

1
#238: The Many Problems in Dealing with Data Problems 45:49

2M ago45:49

45:49

The data has problems. It ALWAYS has problems. Sometimes they're longstanding and well-documented issues that the analyst deeply understands but that regularly trip up business partners. Sometimes they're unexpected interruptions in the data flowing through a complex tech stack. Sometimes they're a dashboard that needs to have its logic tweaked whe…

1
#237: Crossing the Chasm from the Data to Meaningful Outcomes with Kathleen Maley 1:04:44

3M ago1:04:44

1:04:44

The backlog of data requests keeps growing. The dashboards are looking like they might collapse under their own weight as they keep getting loaded with more and more data requested by the business. You're taking in requests from the business as efficiently as you can, but it just never ends, and it doesn't feel like you're delivering meaningful bus…

1
#236: The AI Ecosystem with Matthew Lynley 1:04:36

3M ago1:04:36

1:04:36

Aptiv, Baidu, Cerebras, Dataiku… we could keep going… and going… and going. If you know what this list is composed of (nerd), then you probably have some appreciation for how complex and fast moving the AI landscape is today. It would be impossible for a mere human to stay on top of it all, right? Wrong! Our guest on this episode, Matthew Lynley, d…

1
#235: 2023 Year in Review with Josh Crowhurst 1:06:54

4M ago1:06:54

1:06:54

For those who celebrate or acknowledge it, Christmas is now in the rearview mirror. Father Time has a beard that reaches down to his toes, and he’s ready to hand over the clock to an absolutely adorable little Baby Time when 2024 rolls in. That means it’s time for our annual set of reflections on the analytics and data science industry. Somehow, th…

1
#234: Establishing Expectations for Analysts 1:00:41

4M ago1:00:41

1:00:41

It would be a fool's errand to try to list out every expectation for an analyst's role, but where should you draw the line? How specific do you need to be? And how can you document the unspoken expectations without stepping into micromanagement? Tim, Moe, and Julie took a run at hashing these questions out in our most recent episode so you don't ha…

1
#233: Analytics Mentors (Having One, Being One) 51:31

5M ago51:31

51:31

To mentor, or not to mentor, that is the question: whether 'tis more productive to hole up in a cubicle and toil away without counsel, or to hold close one's experience to the benefit of no one else. Perchance, the author of this show summary should have checked with one of his mentors before attempting a Shakespearian angle. But, he didn't, and th…

1
#232: The Reality of Uncertainty Meets the Imperative of Actionability with Michael Kaminsky 57:48

5M ago57:48

57:48

It's been said that, in this world, nothing is certain except death and taxes, so why is it so hard to communicate uncertainty to stakeholders when delivering an analysis? Many stakeholders think an analysis is intended to deliver an absolute truth; that if they have just enough data, a smart analyst, and some fancy techniques, that the decision th…

1
#231: Estimating the Effort for Analytics Projects 1:02:15

6M ago1:02:15

1:02:15

Have you ever noticed that recipes that include estimates of how long it will take to prepare the dish seem to dramatically underestimate reality? We have! And that’s for something that is extremely knowable and formulaic — measure, mix, and cook a fixed set of ingredients! When it comes to analytics projects, when you don't know the state of the d…

1
#230: First, We Must Discover. Then, We Can Explore. With Viyaleta Apgar 55:10

6M ago55:10

55:10

Seemingly straightforward data sets are seldom as simple as they initially appear. And, many an analysis has been tripped up by erroneous assumptions about either the data itself or about the business context in which that data exists. On this episode, Michael, Val, and Tim sat down with Viyaleta Apgar, Senior Manager of Analytics Solutions at Inde…

1
#229: Data and the ABCs (SERIES A, B, and C, That Is!) with Samantha Wong 52:32

7M ago52:32

52:32

Most of the time, we think of analytics as taking historical data for a business, munging it in various ways, and then using the results of that munging to make decisions. But, what if the business has no (or very little) historical data… because it's a startup? That's the situation venture capitalists — especially those focused on early stage star…

1
#228: What AI Can't Do with Dr. Brandeis Marshall 52:02

7M ago52:02

52:02

It's a lot of work to produce each episode of this show, so we were pretty sure that, by this time, we would have just turned the whole kit and kaboodle over to AI. Alas! It seems like the critical thinking and curiosity and mixing of different personalities in a discussion are safely human tasks… for now. Dr. Brandeis Marshall joined Michael, Juli…

1
#227: Demystifying Complex Data Science Concepts for Non-Technical Audiences with Dr. Nicholas Cifuentes-Goodbody 1:01:09

8M ago1:01:09

1:01:09

One of the biggest challenges for the analyst or data scientist is figuring out just how wide and just how deep to go with stakeholders when it comes to key (but, often, complicated) concepts that underpin the work that's being delivered to them. Tell them too little, and they may overinterpret or misinterpret what's been presented. Tell them too m…

1
#226: Training Analysts to be Curious and Use Business Context with MaryBeth Maskovas 58:03

8M ago58:03

58:03

We were curious about… curiosity. We know it's a critical trait for analysts, but is it an innate characteristic, a teachable skill, or some combination of both? We were curious. How can the breadth and depth of a candidate's curiosity be assessed as part of the interview process? We were curious. Who could we kick these questions (and others) arou…

1
#225: From Stakeholder Buy-In to Stakeholder Knowledge of What That Means 53:36

9M ago53:36

53:36

This topic was such a big deal that we managed to have no guests, and yet we had five people on the mic! Why? Because this episode doubles as a marker of a shift in the show itself. Beyond that, though, we had a lively discussion about how every business stakeholder professes to being committed to being data driven. That should make every stakehold…

1
#224: The Chronic Undervaluing of Analyst Communication Skills 57:35

9M ago57:35

57:35

On the one hand, analysts generally know and accept that part of their responsibility is to not only conduct analyses, but to effectively communicate the results of those analyses to their stakeholders. On the other hand, "communication" can feel like a pretty squishy and nebulous skill. On this episode, Michael, Moe, and Tim tackled that nebulosit…

1
#223: Explainability in AI with Dr. Janet Bastiman 57:33

9M ago57:33

57:33

To trust something, you need to understand it. And, to understand something, someone often has to explain it. When it comes to AI, explainability can be a real challenge (definitionally, a "black box" is unexplainable)! With AI getting new levels of press and prominence thanks to the explosion of generative AI platforms, the need for explainability…

1
#222: A is for… Analytics. Agency. Acquisitions! with Bob Morris 1:08:37

10M ago1:08:37

1:08:37

There comes a time in every analyst's career where they consider starting up their own consultancy. Or, if not that, then at least joining an agency or a consultancy. The nature of most businesses is to grow, and with growth comes the potential for an "exit." This episode dives into that world in an attempt to demystify some of the ins and outs of …

1
#221: Causal Inference Revisited (...DAGnabbit!) with DJ Rich 56:18

10M ago56:18

56:18

What causes us to keep returning to the topic of causal inference on this show? DAG if we know! Whether or not you're familiar with directed acyclic graphs (or… DAGs) in the context of causal inference, this episode is likely for you! DJ Rich, a data scientist at Lyft, joined us to discuss causality — why it matters, why it's tricky, and what happe…

1
#220: Product Management for Data Products and Data Platforms with Austin Byrne 1:02:20

11M ago1:02:20

1:02:20

Data gets accessed and used in an organization through a variety of different tools (be they built, bought, or both). That work can be quick and smooth, or it can be tedious and time-consuming. What can make the difference, in modernspeak, is the specifics of the "data products" and "data platforms" being used for those tasks. Those specifics, in t…

Podcasts Worth a Listen

Digitalanalytics Podcasts

Podcasts Worth a Listen

1
The Analytics Power Hour

Michael Helbling, Moe Kiss, Tim Wilson, Val Kroll, and Julie Hoyer

1
#243: Being Data-Driven: a Statistical Process Control Perspective with Cedric Chin 1:14:20

1
#242: The Rise and Fall of Data Communities with Pedram Navid 58:37

1
(Bonus) Marketing Analytics Summit Is Nigh! 13:08

1
#241: The Analyst's Underutilized Tool: the Sketchbook with Dan White 1:05:24

1
#240: Asking Better Questions with Taylor Buonocore Guthrie 1:11:56

1
#239: Non-Technical Backgrounds in the Modern Analytical World with Kirsten Lum 1:02:39

1
#238: The Many Problems in Dealing with Data Problems 45:49

1
#237: Crossing the Chasm from the Data to Meaningful Outcomes with Kathleen Maley 1:04:44

1
#236: The AI Ecosystem with Matthew Lynley 1:04:36

1
#235: 2023 Year in Review with Josh Crowhurst 1:06:54

1
#234: Establishing Expectations for Analysts 1:00:41

1
#233: Analytics Mentors (Having One, Being One) 51:31

1
#232: The Reality of Uncertainty Meets the Imperative of Actionability with Michael Kaminsky 57:48

1
#231: Estimating the Effort for Analytics Projects 1:02:15

1
#230: First, We Must Discover. Then, We Can Explore. With Viyaleta Apgar 55:10

1
#229: Data and the ABCs (SERIES A, B, and C, That Is!) with Samantha Wong 52:32

1
#228: What AI Can't Do with Dr. Brandeis Marshall 52:02

1
#227: Demystifying Complex Data Science Concepts for Non-Technical Audiences with Dr. Nicholas Cifuentes-Goodbody 1:01:09

1
#226: Training Analysts to be Curious and Use Business Context with MaryBeth Maskovas 58:03

1
#225: From Stakeholder Buy-In to Stakeholder Knowledge of What That Means 53:36

1
#224: The Chronic Undervaluing of Analyst Communication Skills 57:35

1
#223: Explainability in AI with Dr. Janet Bastiman 57:33

1
#222: A is for… Analytics. Agency. Acquisitions! with Bob Morris 1:08:37

1
#221: Causal Inference Revisited (...DAGnabbit!) with DJ Rich 56:18

1
#220: Product Management for Data Products and Data Platforms with Austin Byrne 1:02:20

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