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Data Radicals

Alation
Data Radicals
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  • Why AI Builders Need a Metadata Goldmine with Chris Aberger, VP at Alation
    The future of business intelligence is being rewritten. Have you ever wondered how AI will unlock the power of unstructured data?In this episode of Data Radicals, host Satyen Sangani is joined by Chris Aberger, newly-minted VP at Alation to discuss building AI-powered data workflows.A startup pioneer, Chris explores the importance of metadata in enhancing AI applications within organizations, the significance of quick iterations, and the evolving role of AI engineers.“ That two-step realization is what's causing a lot of this activity that we're seeing in the market, which is, I know I need to plug into databases. I'm now coming to terms with the fact that this is actually a really tough problem to get right.”Listen to this episode to learn:Why metadata curation and feedback loops are crucial for making AI effectiveThe necessity of a fast-paced, iterative approach in developing AI solutionsHow to enable end-users to become builders through AI and metadata toolsListen now: alation.com/podcast/episodes/ai-builders-metadata-chris-aberger*Satyen’s narration was created using AI--------“People have realized that, okay, like structured data is actually like the hard problem to get right. And all these organizations' really valuable data is inside their databases in the structured formats. We have to figure out how to make this ready for the AI era. And then the kind of second level problem that people are discovering is how do I make this structured data actually work? Oh, it's metadata. And I think that realization that that kind of two-step realization is what's causing a lot of this activity that we're seeing in the market, which is, I know I need to plug into databases. I'm now coming to terms with the fact that this is actually a really tough problem to get right. In order to get it right, I need to effectively go build a data catalog or metadata provider, and therefore we're seeing a lot of activity in this space.” – Chris Aberger--------Time Stamps*(02:04): From the Stanford AI Lab to founding Numbers Station*(12:10): From chat with your data to act with your data: From data users to business builders*(19:23): The value of metadata to production-ready AI*(28:46): What are precision agentic workflows?*(35:35): Empowering enterprise data users to build with AI*(45:50): Satyen’s takeaways--------SponsorThis 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/--------LinksConnect with Chris on LinkedIn
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  • Perfume, Power, Prediction: Inside a Luxury Giant's Data and AI Strategy with Julie De Moyer, Chief Data Officer of LVMH Beauty
    In the luxury world where artistry is key, how is AI enabling personalization, optimization, and speed?In this episode of Data Radicals, host Satyen Sangani is joined by Julie De Moyer, Chief Data Officer of LVMH Beauty to break down the role of data and AI in business transformation.A seasoned strategist and leader of innovation across 15 beauty brands, Julie shares practical examples of AI application in various aspects of LVMH's operations, from product development to supply chain management.“ The AI is often the cherry on the cake. We're moving towards those new technologies that are helping us dream even bigger.”Listen to this episode to learn:The importance of collaboration, change management, and consumer-centric approaches.How to work closely with CEOs to drive meaningful data-driven decisions.How to balance AI and human creativity within the luxury beauty industry.Listen now: https://www.alation.com/podcast/episodes/lvmh-data-ai-strategy-julie-de-moyer*Satyen’s narration was created using AI**LVMH is vendor-neutral and this does not constitute an endorsement**All views and opinions expressed by the speakers are their own--------“ If you look at the making of perfumes or the way we actually make the wines, in other industries, we would use the AI in order to help those, I would say, those scientists to go faster, to optimize their trials. It will never replace the final scent or the final product that is decided on, but it can help with the substitutions of products that might need to go out, as a result of regulatory changes. It might also help with making sure that the quality of the products last as long as possible. We really help those researcher scientists do their job better and easier.” – Julie De Moyer--------Time Stamps*(01:34): Julie’s background: From economics student to technology leader*(07:55): AI in action: How stakeholders collaborate*(14:42): The role of data in luxury today (and 5 ways to apply AI in retail)*(22:09): Leading data in a multi-brand environment*(28:18): How to become a trusted AI leader: Key tips*(33:40): Satyen’s takeaways--------SponsorThis 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/--------LinksConnect with Julie on LinkedIn
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  • The Rise of AI: Voices from the Frontlines
    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.--------“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--------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--------SponsorThis 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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  • Delegate to Innovate: How Letting Go Makes You a Better Leader with Todd James, Founder & CEO of Aurora Insights
    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--------“ 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--------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--------SponsorThis 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/--------LinksConnect with Todd on LinkedInLearn more about Aurora Insights
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  • Data Products for Dummies with Sanjeev Mohan, Principal at SanjMo
    What if the future of data management isn’t just about governance—but about growth, speed, and strategic advantage? From reshaping data operations to unlocking new levels of productivity, data products and AI agents are redefining what’s possible in the world of data.In this episode of Data Radicals, Satyen Sangani sits down with Sanjeev Mohan, Principal at SanjMo, to discuss the definition, impact, and lifecycle of data products. They also examine how AI agents are revolutionizing job functions and industries, and practical applications for harnessing this technology’s full potential.Listen to this episode to learn:What data products are and their importance in delivering measurable value, building trust, and improving user experience.The challenges in adopting data products, including the need for a cultural shift within organizations and the potential resistance to change.How generative AI and autonomous agents can revolutionize data management, business processes, and job functions.Discover how forward-thinking data leaders are using these tools not just to manage data—but to build trust, accelerate outcomes, and drive measurable business value.*Satyen’s narration was created using AI--------“ The systems that are running really well, in a lot of organizations, why would they rip out and then go down the path of data products? Because, the problem with data products is it's also a cultural issue. It's a mindshift and you have to think from a completely different long-term point of view. We are so used to – in IT – somebody gives me a problem, I'm like, ‘Yes, I got it. I'll solve it for you.’ Then you move on to the next problem. With data products, it's a mindset shift.” – Sanjeev Mohan--------Time Stamps*(02:28): What is a data product?*(12:30): Why data products demand a mindset shift in IT*(27:19): What is an AI agent?*(36:39): How will data management evolve with the advent of AI?*(47:56): Satyen’s takeaways--------SponsorThis 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/--------LinksConnect with Sanjeev on LinkedInLearn more about SanjMoDownload Sanjeev’s book Data Products for DummiesSubscribe to Sanjeev’s podcast It Depends
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About Data Radicals

Some people can see things that nobody else can. They seem to be able to peer around corners and into the future. These seemingly super powers come from being able to synthesize the data all around us. They approach problems with a curious and rational mind. They think differently and encourage others to embrace data culture. We call them “data radicals” because they transform themselves and the world around them In this podcast, we talk to these Data Radicals to understand what makes their approach so unique and how it can be replicated.
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