Summary
- The Analytics Power Hour for real-world insights.
- Super Data Science for deep technical learning.
- Hub & Spoken for strategy and leadership.
- Ken’s Nearest Neighbors for career growth.
- Data Stories for mastering data visualization and storytelling.
Staying sharp in data analytics isn’t easy. The field is shifting every quarter:
- New tools.
- New models.
- New “must-know” best practices.
And let’s be honest, nobody’s got time to read every whitepaper or watch every conference replay. That’s where podcasts are the users’ best friends. Whether you’re commuting, working out, or making coffee, they’re a smart way to pick up insights without stopping your day.
But this isn’t just a random list. We’ve grouped the best shows into categories. Whether you’re just building the analytics foundation, diving deep into ML and engineering, or stepping into leadership territory. You’ll find the right voices, at the right level, for where you are (and where you’re headed).
Ready to plug in? Let’s get into the top data analytics podcasts worth your playlist in 2026.
Table of contents
- Podcasts for Building Your Data Foundations
- Deep Dive: Technical Podcasts for Practitioners
- From Data to Decisions: Podcasts for Leaders
- Niche Listens: Podcasts with a Special Focus
- Conclusion
Podcasts for Building Your Data Foundations
The Analytics Power Hour
Why we chose it
This one’s like grabbing coffee with a group of smart, opinionated analysts who’ve seen it all. The hosts talk through the messy, human side of analytics. Stakeholder drama, dashboard politics, measuring what actually matters. It’s refreshingly honest and full of “yep, been there” moments.
Who should listen
Perfect for junior analysts, students, or anyone new to the field who wants to learn what real analytics work actually looks like, not just the theory.
Ken’s Nearest Neighbors
Why we chose it
Ken brings on everyone from data YouTubers to senior ML engineers, and the conversations feel like mentorship sessions you wish you had earlier. Packed with lessons on breaking into data, building portfolios, fighting imposter syndrome, and navigating career pivots.
Who should listen
Ideal for aspiring data scientists and analysts trying to figure out how to stand out, land interviews, and grow beyond the entry level, one story at a time.
Deep Dive: Technical Podcasts for Practitioners
Super Data Science
Why we chose it
Hosted by Kirill Eremenko, this podcast is like an ongoing masterclass in everything from AI and ML to data engineering. Each episode explains technical topics in a detailed but still easy-to-follow way, making it perfect for brushing up your skills on the go. You’ll often hear from real-world practitioners, not just theorists, which keeps it grounded and practical.
Who should listen
A great fit for data scientists, ML engineers, and developers who want to stay on top of trends and sharpen their technical toolkit.
Data Stories
Why we chose it
If you’ve ever geeked out over the craft of data visualization, this one’s for you. Hosts Enrico Bertini and Moritz Stefaner dive deep into how to turn data into meaning, exploring everything from chart design to visual storytelling. The conversations are smart, funny, and full of hands-on takeaways you can use right away.
Who should listen
BI developers, analysts, or anyone passionate about data storytelling and visual communication.
Alter Everything
Why we chose it
Backed by Alteryx, this podcast takes a wide-angle view of analytics culture. It touches on AI, automation, and data literacy, but what really makes it stand out is how it ties the tech back to people and process. You’ll hear from both industry leaders and data pros in the trenches.
Who should listen
Best suited for data professionals who use tools like Alteryx, Tableau, or Power BI, or anyone who wants to stay inspired by how analytics is reshaping business from the inside out.
From Data to Decisions: Podcasts for Leaders
Hub & Spoken: Data | Analytics | Chief Data Officer | CDO | Data Strategy
Why we chose it
Hosted by Jason Foster, this show brings together some of the brightest minds in data leadership. Each episode dives into how organizations turn raw data into business value, covering governance, data culture, and the evolving role of the Chief Data Officer. It’s less theory and more “how we actually did it.”
Who should listen
Perfect for CDOs, analytics managers, and business leaders who want to translate data strategy into measurable impact.
Secrets of Data Analytics Leaders
Why we chose it
Wayne Eckerson’s interviews feel like fireside chats with industry veterans from global enterprises. He uncovers how these leaders built their analytics programs, overcame organizational resistance, and delivered tangible business outcomes. Real talk, no fluff.
Who should listen
A must-listen for current and aspiring data leaders aiming to sharpen their leadership edge and learn from the people who’ve already cracked the code.
The Data Scientist Show
Why we chose it
Even though new episodes are on pause, the existing catalog is a goldmine. Host Daliana Liu sits down with data scientists from companies like Google, Airbnb, and Meta to unpack their journeys, technical challenges, and lessons learned from the front lines. The tone is approachable yet deeply insightful.
Who should listen
Ideal for data scientists or engineers looking for career inspiration, learning how leaders think, and understanding what it really takes to scale in big-data environments.
Niche Listens: Podcasts with a Special Focus
Women in Analytics After Hours
Why we chose it
This podcast is a fresh look at women’s journeys in data and analytics. Here, you’ll know more about leadership, career growth, and navigating technical roles while staying authentic about real challenges. It’s not just about gender diversity. It’s about the diverse paths people take to succeed in data.
Who should listen
Anyone in the analytics community who values diverse perspectives and wants to hear honest, energizing stories from women driving change in the field.
The Marketing Intelligence Show
Why we chose it
At the crossroads of marketing and data, this show is a goldmine for anyone looking to turn analytics into real business outcomes. Each episode explores how data-driven strategies can boost customer engagement, ROI, and creative decision-making. The guests are often practitioners who’ve actually built and scaled data-backed marketing operations.
Who should listen
Marketing analysts, growth marketers, and business leaders who want to harness analytics to make smarter marketing moves and drive measurable impact.
Conclusion
In this list, every kinds of data professional can find a podcast out there. Whether you’re building a solid foundation, diving deep into AI and engineering topics, or shaping analytics strategy at scale, these shows will keep you learning on the go. Try mixing a few. One for technical depth, another for big-picture strategy, and you’ll stay sharp in a field that never stands still.
And remember, podcasts are just one piece of the data puzzle. Platforms like Skyvia make it easier to bring all your data together, so the insights you hear about in these episodes can actually come to life in your own dashboards and decisions.
Ready to turn data inspiration into action? Explore Skyvia and see how simple data integration can power your next big idea.
F.A.Q. for Top 10 Data Analytics Podcasts
Are there any data analytics podcasts that focus specifically on data visualization?
Yes, Data Stories. It dives deep into data visualization and storytelling with insights from field experts.
Which podcasts are best for experienced data leaders and managers?
Hub & Spoken and Secrets of Data Analytics Leaders . Both focus on data strategy, leadership, and decision-making.
What technical topics do these data analytics podcasts cover?
From AI, ML, and data engineering (Super Data Science) to workflow automation and data literacy (Alter Everything).
Are there any podcasts that feature diverse voices in the data community?
Definitely, Women in Analytics After Hours showcases stories and insights from women shaping the analytics industry.
