Data Radicals
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Top 10 Data Radicals Episodes
Goodpods has curated a list of the 10 best Data Radicals episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to Data Radicals for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite Data Radicals episode by adding your comments to the episode page.
02/21/24 • 41 min
The rapid progress in AI technology has fueled the evolution of new tools and platforms. One such tool is a vector search. If the function of AI is to reason and think, the key to achieving this is not just in processing data, but also in understanding the relationships among data. Vector databases provide AI systems with the ability to explore these relationships, draw similarities, and make logical conclusions. Understanding and harnessing the power of vector databases will have a transformative impact on the future of AI.
Edo Liberty is optimistic about the future where knowledge can be accessed at any time. Edo is the CEO and Founder of Pinecone, the managed database for large-scale vector search. Previously, he was a Director of Research at AWS and Head of Amazon AI Labs, where he built groundbreaking machine learning algorithms, systems, and services. He also served as Yahoo's Senior Research Director and led the research lab building horizontal ML platforms and improving applications. Satyen and Edo give a crash course on vector databases: what they are, who needs them, how they will evolve, and what role AI plays.
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“We as a community need to learn how to reason and think. We need to teach our machines how to reason and think and talk and read. This is the intelligence and we need to teach them how to know and remember and recall relevant stuff. Which is the capacity of knowing and remembering. The question is, what does it mean to know something? To know something is to be able to digest it, somehow to make the connections. When I ask you something about it, to figure out, ‘Oh, what's relevant? And I know how to bring the right information to bear so that I can reason about it.’ This ping pong between reasoning and retrieving the right knowledge is what we need to get good at.” – Edo Liberty
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Time Stamps
*(03:13): How vector databases revolutionize AI
*(14:13): Transforming the digital landscape with semantic search and LLM integration
*(28:10): Exploring AI’s black box: The challenge of understanding complex systems
*(37:02): Striking a balance between AI innovation and thoughtful regulation
*(40:01): Satyen’s Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile:
https://www.linkedin.com/in/ssangani/
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Links
From Back Office to Boardroom: The CDO's AI Opportunity with Ryan den Rooijen & Wade Munsie
Data Radicals
03/19/25 • 57 min
As technology rapidly evolves and businesses focus on getting real results, data jobs are shifting. Many data tasks now fall under the CIO or CTO, data leaders are moving into roles that affect bigger business plans, and more companies are using self-service data tools or seeking a path to AI—making CDO-led teams less necessary. How can data leaders adapt?
In this episode of Data Radicals, Satyen Sangani talks with Ryan den Rooijen, Writer and Consultant at Qstar.ai, and Wade Munsie, Interim Director of Data & AI at Heathrow. With years of experience in data leadership, Ryan and Wade explore how the CDO role is changing, the challenges in data and AI, and why the job isn’t always what people expect.
Listen to this episode to learn:
- The future of data leadership, including how AI is changing the way we use data and why it's important to stay flexible and focused on real business results.
- Why data leaders need to go beyond their usual tasks and help improve the whole business.
- How AI and smart computer systems are shaping data management and what these new technologies could mean for the future of the industry.
From capitalizing on generative AI to redefining the CDO role, this episode offers a wealth of knowledge for anyone looking to understand the real-world challenges and opportunities in the data landscape. Tune in to hear practical advice and visionary thoughts from top data leaders.
*Satyen’s narration was created using AI
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“ For many of these organizations, there really is an onus on people like ourselves to prove ourselves in the organization. I think the biggest data culture challenge is really how do we make ourselves relevant to the day-to-day of the employee? How do we make sure that if somebody is on an oil rig or in a store or in a call center or on a trading floor or in a lab, they are going to do something different because of us? Because if they're not doing something different because of us, then honestly, we don't deserve to be here.” – Ryan den Rooijen
“ Traditionally, CDOs were in place to wrangle and collate the data and curate the data to a point that it was perfect. That was the ideal for a long time. I think that's probably an impossible task these days with all the different types of unstructured data around there. But also, is it needed? If we keep pushing for that nth degree, you are never going to achieve it. If you keep pushing for that from a quality point of view and a curation point of view, you forget about why you were there in the first place, which is value. If you don't get to that value point quick enough, it's very hard to explain why you were owed that budget in the first place, where all that cost went.” – Wade Munsie
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Time Stamps
*(02:23): Why is the chief data officer in trouble?
*(12:00): The CDO as a transformational role
*(23:52): Redefining data culture as value-driven
*(32:50): Data leaders as systems thinkers
*(45:09): How will AI impact data teams?
*(55:48): Satyen’s Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Read Ryan and Wade’s MIT Sloan article The Chief Data Officer Role: What’s Next
Read Ryan and Wade’s series Chief Data Officers Are In Trouble
Delegate to Innovate: How Letting Go Makes You a Better Leader with Todd James, Founder & CEO of Aurora Insights
Data Radicals
04/30/25 • 49 min
What does it take to turn AI hype into operational value at enterprise scale?
In this episode of Data Radicals, host Satyen Sangani sits down with Todd James, former Chief Data and Technology Officer at 84.51° and Kroger executive, to unpack the realities of leading AI transformation inside one of America’s largest grocery retailers.
Drawing on a career that spans the Coast Guard, consulting, and Fortune 100 leadership, Todd shares how scaling AI isn’t just about building advanced algorithms—it’s about solving real problems, embedding with the business, and building reusable infrastructure that lasts.
“If the people at the consumption end of your sciences aren’t bought in, they don’t get implemented.”
Listen to this episode to learn:
- How effective leaders “delegate to innovate” and create space for team growth
- How AI reduced Kroger’s pick-order travel time by 10% and truck route distance by 8.6%
- Why the CDO role is likely transitional—and what’s next for data leadership
- What it takes to embed data science into the operational core of a business
This conversation is a must-listen for anyone building AI programs, leading data teams, or navigating digital transformation.
Listen now: https://www.alation.com/podcast/episodes/delegate-innovate-todd-james
*Satyen’s narration was created using AI
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“ I think we should go into every project, every initiative, saying, ‘I own an outcome around bringing people along and convincing them.’ If you're doing that right, you're probably spending more than half of the project or half the initiative on managing those organizational dynamics. Working with people and how they think and how they feel to be able to drive them to an outcome to listen. I think that's more than half the work that needs to happen in the space. We talk about data and analytics and how hard the math is and how cool the outcomes are, but this is transformation. This is about people.” – Todd James
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Time Stamps
*(01:46): Todd’s career journey: From the Coast Guard to Fidelity
*(10:03): Great leaders delegate: Advice for aspiring executives
*(12:53): AI retail use cases: Quicker routes and personalization at scale
*(26:12): Reapplying data-science processes across distinct problems
*(40:21): Is the CDO role transitional?
*(48:27): Satyen’s takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
If you’re a history buff in the data world, you know that there’s a complex interplay between data, statecraft, and machine learning. The history of data visualization is entwined with societal governance and technological advancements, starting from the usage of statistics for statecraft in the 18th century to the transformative innovations during World War II that birthed computation and data science as we know it. And because of the subjective design choices that underpin data gathering and analysis, there’s an inherently political nature of deciding what data to collect and how to utilize it, which is critical in understanding both historical and contemporary data practices.
As we move into the modern applications of data science and the advent of AI technologies, deep reinforcement learning and the integration with generative AI models, these technologies are reshaping the field by enabling computers to process and interact with unstructured data in unprecedented ways. Satyen and Chris discuss his book How Data Happened, the origins of data science and the role of Alan Turing in the creation of digital computing, and the challenges generative AI brings around model interoperability.
*Satyen’s narration was created using AI
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“In the last two years, one of the major techniques for advancing the most eye-popping products has been RLHF, Reinforcement Learning from Human Feedback. There's innumerable subjective design choices happening there, which eventually become encoded in a product. But, the presentation of it as though it's somehow unbiased and free from any subjective design choices is illusory.” – Chris Wiggins
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Time Stamps
*(01:36): How did Chris come to write How Data Happened?
*(10:33): World War II as the springboard for data science and digital computing
*(18:37): The tension between objectivity and subjectivity in data today
*(25:36): What is Reinforcement Learning from Human Feedback (RLHF)?
*(36:03): How has Gen AI impacted data science?
*(44:53): Satyen’s takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile:
https://www.linkedin.com/in/ssangani/
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Links
The Reign of Specialists is Over with David Epstein, Best-Selling Author of Range and The Sports Gene
Data Radicals
01/19/22 • 32 min
Growing up, we’re all asked what we want to be when we’re older. Our answer is normally met with an explanation of the years of education and dedication we’ll have to go through to get there. Whether it’s trade school, medical school, a PhD, or apprenticeship, we start to understand that we’ll need years of specialized training to get to where we want to be. But what if that whole way of thinking is wrong?
Today, we’re learning to completely shift our approach to the understanding of expertise. Our guest is David Epstein, bestselling author of Range: Why Generalists Triumph in a Specialized World and The Sports Gene: Inside the Science of Extraordinary Athletic Performance. He shares why you should shift your focus from being a specialist to a generalist, and how that can exponentially increase your odds for success. You won’t want to miss it.
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"The people who are good forecasters sometimes have an area of specialty, sometimes they don't, but more important than what they think, is how they think." - David Epstein
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Time Stamps
(0:00) How Satyen became a generalist
(2:52) Why IQ tests aren’t as helpful as you think
(5:53) What makes an environment kind or wicked
(13:23) Getting comfortable with sporadic success
(18:31) The perks of generalization
(22:57) The shortcomings of specialization
(26:36) What we can learn from Vincent Van Gogh
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Sponsor
This podcast is presented by Alation.
Learn more:
Data Radicals: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Data Governance: Any “Dummy” Can Do It! with Dr. Jonathan Reichental, Author & Founder of Human Future
Data Radicals
03/29/23 • 49 min
Data governance is often seen as a confusing topic but everyone, even dummies, are capable of applying it to their organization. By starting with the “why” and acting on the most critical pieces, you can build a successful data governance initiative.
In this episode, Satyen interviews Dr. Jonathan Reichental, author of Data Governance for Dummies and Founder of Human Future. He is an Adjunct Professor at several universities, including the University of San Francisco, Pepperdine University, and Menlo College. Dr. Reichental also served as the Chief Information Officer at both O’Reilly Media and the city of Palo Alto, California. Satyen and Dr. Reichental discuss implementing data governance step-by-step, avoiding common governance pitfalls, and the future of smart cities.
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“I do think in the long run though, data governance is not about a narrow target. You will build a better business if you hire all the right people, if you build the right products, and deliver the right services, not by doing just one thing and doing it really well. It's a comprehensive approach to running a successful business, as you know well. And I think data governance should be thought of in the short term as targeting some very specific things, but long term as a cultural shift in how you actually think about data and how you use data on the backend and in the front end of your business.” – Dr. Jonathan Reichental
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Time Stamps:
*(01:34): Dr. Reichental dives into his book Data Governance for Dummies
*(08:51): How to convince people to invest in data
*(13:27): Dr. Reichental defines data governance and how it relates to data management
*(24:11): The signs a data culture is ready for governance
*(42:42): Dr. Reichental’s opinion on cryptocurrency and blockchain
*(47:20): Satyen’s Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile:
https://www.linkedin.com/in/ssangani/
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Links
04/26/23 • 58 min
There are some things that just can’t be quantified by data; imagine trying to portray your childhood in a spreadsheet! Yet these experiences are valuable. How can data teams capture qualitative information – and use it to steer the business? It starts with getting your data team out of the building. Only then can they gain insights about customer pain points and what the data is failing to tell us.
In this episode, Satyen interviews Tricia Wang, a “tech ethnographer” and co-founder of Sudden Compass, a consulting firm helping companies improve their business through thick data. She also co-founded CRADL (Crypto Research and Design Lab) with the mission to create inclusive and sustainable growth of the crypto ecosystem. Satyen and Tricia discuss the power of thick data, the value of digital personhood, and the dangers of quantification bias.
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“Your job as a Chief Data Officer or a data leader in the company is, data is only part of your job generating the quantification to reflect back to the company. The other half is the bleeding edges around communication and helping the rest of your business, your business counterparts, to understand the value of this in a way that isn't scary and where they can see that it actually is going to improve their business. [...] But that takes a really brave kind of leader to work that way because it's not just about having the light shine on you, but it's about you making others and your company successful.” – Tricia Wang
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Time Stamps:
*(01:35): The role of a tech ethnographer
*(15:29): Tricia gives a rundown of thick data
*(23:06): Understanding customers by getting out of the building
*(32:36): Why quantification bias is dangerous to growth
*(44:48): The importance of digital personhood
*(57:22): Satyen’s Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
06/07/23 • 47 min
As human beings, we’re not accustomed to talking about data. In order to learn about new subjects, we traditionally use stories. However, bridging the gap between data and stories allows us to cross that barrier and create data-driven organizations.
In this episode, Satyen interviews Ashish Thusoo, GM of AI and ML at AWS. Previously, Ashish was the Founder and CEO of Qubole, a pioneering cloud data lake platform. He also served Facebook as the Engineering Manager of Data Infrastructure where he co-created Apache Hive with the aim to democratize data access and analytics. Satyen and Ashish discuss the accelerated push to the cloud, building a data culture, and how the economic climate is impacting customers.
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“You have to remember, human beings are trained from the get-go to talk about stories, not data. That's how we learn. It takes special discipline to bring the conversation back to data, saying that, ‘You have this anecdote somewhere. Get me the data that proves or disproves it.’ That specific mindset has got to be inserted in the organization, and that's how it becomes data-driven. It's a very fine line, but if you cross that line, essentially you become a data-driven organization. But, if you stay on the side of anecdotes and stories, then you can't bridge that.” – Ashish Thusoo
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Time Stamps:
*(02:33): The SQL excitement that powered Hive
*(13:42): The evolution of Qubole’s founder hypothesis
*(22:48): Navigating Amazon with AI/ML
*(31:41): The future of AI/ML investment
*(42:01): People are the foundation of the data culture
*(45:57): Satyen’s Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Asking the Right Questions with Frank Farrall, Principal, AI/Data Ecosystems at Deloitte
Data Radicals
07/05/23 • 46 min
Before search engines, we had to rely on memory and investigation to answer our questions. Then, search engines made answers instantly available. Now, in the age of AI, we have to engineer our questions to get the best results.
Frank Farrall, Deloitte's Strategy & Analytics Ecosystems and Alliances Leader, knows that asking the right questions is just as critical as knowing the answers. Frank is a global business builder with 20 years of experience helping clients and startups become billion-dollar businesses through AI and digital transformation.
In this episode, Satyen and Frank discuss identifying worthy investments, the sexiness of prompt engineering, and efficient engagement with AI.
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“I think in a lot of cases, prompt engineering will at least become a skill that knowledge workers, creative workers use to get an outcome from the technology. I think some people will be highly, highly specialized. I actually think prompts are going to have value in organizations and I think prompt libraries and how you manage prompts will become a set of IP and something that's highly valuable inside organizations. I think prompt engineering has a very significant future ahead of it. I think all of us are going to have to learn some level of prompt engineering to be effective in the future.” – Frank Farrall
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Time Stamps:
*(02:42): Defining the AI ecosystem
*(07:55): How to identify a worthy investment
*(23:23): How “sexy” is prompt engineering?
*(41:44): The future of generative AI
*(44:43): Satyen’s Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile:
https://www.linkedin.com/in/ssangani/
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Links
The Rise of AI: Voices from the Frontlines
Data Radicals
05/14/25 • 38 min
In this special compilation episode, we're bringing together the most insightful conversations from our latest season exploring the rise of AI. You'll hear from thought leaders like Fortune's AI editor Jeremy Kahn on rebuilding the middle class, marketing executive Michael Olaye on creative acceleration, and Tom Davenport on what real AI transformation looks like. Plus insights from numerous other AI experts including CDOs, academics, and tech entrepreneurs who are shaping our AI future today.
We'll explore practical AI use cases, examine how data leaders can leverage these technologies, and discuss how the CDO role is evolving in response to AI's momentum.
Listen to this episode to learn:
- How AI copilots are fundamentally changing the way we work and uplifting workers across industries.
- Why it's important to have data leaders who can translate between technical possibilities and business realities.
- How solid data infrastructure, clear business objectives, and thoughtful human oversight leads to successful AI transformation.
Whether you're a data professional, business leader, or simply curious about AI's impact, this episode offers perspectives from those on the frontlines of the AI revolution.
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“I think this is gonna be a tremendously transformative technology, and I think there's some really big positive effects, particularly I think we are gonna see a huge uplift in labor productivity, and I don't think we're gonna see sort of mass joblessness from this technology. I think actually this is a technology that could enable people to sort of be lifted back up into the middle class.” – Jeremy Kahn
“You can do stuff that would take weeks before in days. You can collaborate with people who have no technical knowledge on technical things. We have tools now that you can code by like verbally speaking natural language. We have tools that you can do design without having any design skills. So, I think it's opened up a whole new site for agencies, consultancies, companies, but it's also opened a whole new site for a new like economy of like content creators. When you build anything with AI, having a human in that loop where we are today, having humans in that loop, checking that also, it's good.” – Michael Olaye
“It's not rocket science. It's having senior people who are interested in analytical, decision making, hiring people who can do the work. The day-to-day work of analytics, both the data management and the data analysis. And ultimately having some sort of unique data that is proprietary to you, that will really differentiate you. Because ultimately data is a fuel of analytics and AI. And if you don't have something distinctive, you're gonna have the same models that everybody else has.” – Tom Davenport
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Timestamps
*(01:18): AI as copilot
*(04:30): AI: It’s still early days
*(06:13): AI Use Cases
*(11:26): How data leaders can leverage AI
*(14:07): Data leadership and systems thinking
*(18:17): The future (and limits) of the CDO
*(29:15): Predictions
*(35:16): Career advice
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
David’s LinkedIn Profile: https://www.linkedin.com/in/davidwchao/
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FAQ
How many episodes does Data Radicals have?
Data Radicals currently has 74 episodes available.
What topics does Data Radicals cover?
The podcast is about Leadership, Data, Podcasts, Technology, Business and Data Science.
What is the most popular episode on Data Radicals?
The episode title 'Multiple Sources of Truth: Decentralization and the Data Mesh with Zhamak Dehghani, Creator of the Data Mesh' is the most popular.
What is the average episode length on Data Radicals?
The average episode length on Data Radicals is 40 minutes.
How often are episodes of Data Radicals released?
Episodes of Data Radicals are typically released every 14 days.
When was the first episode of Data Radicals?
The first episode of Data Radicals was released on Jan 12, 2022.
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