Mavens of Data

In this episode, we're joined by Terry Dorsey, Senior Data Architect & Evangelist at Denodo, to unpack the conceptual differences between terms like data fabrics, vector databases, and knowledge graphs, and remind you not to forget about the importance of structured data in this new AI-native world! What You'll Learn: The difference between data fabrics, vector databases, and knowledge graphs — and the pros and cons Why organizing and managing data is still the hardest part of any AI project (and how process design plays a critical role) Why structured data and schemas are still crucial in the age of LLMs and embeddings   How knowledge graphs help model context, relationships, and "episodic memory" more completely than other approaches   If you've ever wondered about different data and AI terms, here's a great glossary to check out from Denodo: https://www.denodo.com/en/glossary 🤝 Follow Terry on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Data scientists have the skills to model complex systems, work with messy data, and uncover hidden patterns. Quant scientists do all of that, but with the added thrill (and pressure) of putting real money on the line. In this episode, we sit down with Jason Strimpel, Founder of PyQuant News and Co-founder of Quant Science, to explore why data scientists are uniquely positioned to excel in algorithmic trading. Whether you're a data scientist curious about finance, or simply interested in seeing your models have a more personal impact, this show offers a fresh perspective on how your skills can translate into the world of algorithmic trading. What You'll Learn: How your Python, stats, and modeling skills transfer directly into the markets The mindset shifts required Why reproducibility, auditability, and backtesting discipline are the data scientist's secret weapon Common pitfalls when transitioning into quant roles, and how to avoid them The tools and workflows Jason recommends to get started fast   🤝 Follow Jason on LinkedIn! Subscribe to PyQuant News   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

In this show, we're joined by Sean Chandler, Director of BI at CenterWell Home Health, to explore what it really means to thrive in BI today. Sean shares his personal journey, including his move into teaching, and offers practical insights on building a career in BI, self-learning for advancement, and fostering a strong partnership between BI and data science teams. Whether you're an aspiring BI analyst, a data scientist aiming to improve collaboration, or a career changer eyeing the BI space, this episode is for you. What You'll Learn: How to successfully transition from other roles into BI, and how to know if it's the right fit for you What good collaboration between BI and data science actually looks like, and how to recognize when it's broken How self-taught skills can accelerate your BI career, even without a formal background   🤝 Follow Sean on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

AI isn't just accelerating productivity, it's reshaping how we structure power, make decisions, and define what "value" means in our organizations. In this episode, Felicia Newhouse — a data leader, AI strategist, and advocate for ethical, human-centered innovation — brings deep insight into how power structures in business are being reimagined in the age of AI. We dive into why so-called soft skills like communication, critical thinking, and emotional intelligence are becoming core differentiators in data and AI teams. With research showing that companies deploying AI without leadership transformation risk ethical blind spots and cultural misalignment, we ask: What kind of leaders do we need now? And how can data professionals step into that shift? What You'll Learn: Why soft skills are no longer optional in data and AI roles How leadership, ethics, and communication shape responsible AI outcomes Real-world examples of companies gaining trust and performance by elevating human-centered skills   🤝 Follow Felicia on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

If you're thinking about Data Analyst or Data Scientist career paths, then this one is for you! In this episode with Data Career Jumpstart Founder Avery Smith, you'll learn about the differences between Analyst and Data Scientist career paths, and hear some practical advice to help you on your journey. You'll leave with a better understanding of different data roles, which might be the better fit for you, and a concrete roadmap for taking action and accelerating your career. What You'll Learn: Key differences between Data Analyst and Data Science roles The critical tools to focus on to land a job in either role A step by step playbook for building the skills you need to succeed   This session was part of our OPEN CAMPUS week in October, which included 6 days of live expert sessions.   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

From launching AI products to modernizing legacy data stacks, we're going behind the scenes of data-driven transformation in financial remittance. In this episode, we sit down with Sia Zahedi, former CDO at a global financial remittance company, to get a candid look at the projects, challenges, and decisions that define data leadership in finance. If you've ever wondered what it's like to lead data strategy at a global financial company, this one is for you. What You'll Learn: What the day-to-day of a CDO looks like Real-world use cases for AI in financial services The difference between launching AI prototypes and real products Career advice for aspiring CDOs and senior data leaders   🤝 Follow Sia on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Ken Jee has spent a decade in sports analytics, working at the intersection of data science and athlete performance. Now, he's building The Exponential Athlete, a podcast dedicated to exploring what makes athletes reach their highest potential. In this show, Ken shares: His 10-year journey in sports analytics and the lessons data can, and can't teach us about performance. How his background in data science set him up to successfully launch The Exponential Athlete. The limits of analytics — why diagnosis is easy, but decision-making is complex. How mental visualization (seeing success before it happens) plays a crucial role in athletic and personal excellence. The intersection of training philosophy, psychology, and data in shaping elite performers. Whether you're passionate about sports, data science, entrepreneurship, or personal growth, this episode offers practical insights you can apply immediately. 🤝 Follow Ken on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Too many dashboards. Endless ad-hoc questions. Analytics teams often get trapped supporting the business, without driving it forward. In this show, Ollie Hughes, CEO of Count, will show you how to break free. Based on real-world case studies and hard-won experience, Ollie will walk us through: The common traps analytics teams fall into — and why good intentions often lead to low impact  How to shift from "answering questions" to "solving business problems" Why operational clarity, not just better data, is the key to better outcomes. Real use cases and strategies for building high-leverage analytics inside your organization. If you're ready to move beyond dashboards and truly drive business success, this is the show you can't afford to miss. 🤝 Follow Ollie on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

In this episode, we're joined by Maven's own Chris Bruehl to unpack the 2025 data science landscape and explore what it really takes to break into the field today. If you're curious about what data scientists actually do — and how to become one — you won't want to miss this! What You'll Learn: How the data scientist role compares to other data careers The essential skills you need to land a data science job in 2025 Smart strategies to position yourself before applying   🤝 Follow Chris on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

LLMs seem like a hot solution now, until you try deploying one. In this episode, Andriy Burkov, machine learning expert and author of The Hundred-Page Machine Learning Book, joins us for a grounded, sometimes blunt conversation about why many LLM applications fail. We talk about sentiment analysis, difficulty with taxonomy, agents getting tripped up on formatting, and why MCP might not solve your problems. If you're tired of the hype and want to understand the real state of applied LLMs, this episode delivers. What You'll Learn: What is often misunderstood about LLMs The reliability of sentiment analysis How can we make agents more resilient?   📚 Check out Andriy's books on machine learning and LLMs: The Hundred-Page Machine Learning Book The Hundred-Page Language Models Book: hands-on with Pytorch  🤝 Follow Andriy on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

In this episode, we sit down with Joe Dery, Vice President of Customer Success at Aera Technology, to explore a concept that's shifting how organizations think about analytics: Decision Intelligence. We unpack what decision intelligence really means (hint: it's not just another buzzword), why some data scientists still resist it, and how this discipline helps surface causal insights — not just correlations. Joe brings firsthand use cases from the field, showing how DI is helping organizations not only analyze what's happening but also decide what to do about it. Whether you're a data scientist, product manager, or exec who wants to move from dashboards to decisions, this one's for you. What You'll Learn: What decision intelligence is — and what it isn't Why some in the data space push back against it How DI gets you closer to causality (not just correlation) Real-world use cases where DI created business impact Why decision metadata is the secret sauce for long-term success   Follow Joe on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

AI is moving fast, but are organizations prepared to keep up? In this episode, data professional Laura Madsen joins us to unpack why most companies are lagging behind, how tech debt is holding businesses back, and why knowledge graphs are the way forward. Join us for a bold conversation on why the AI revolution needs better data governance, not just bigger models. What You'll Learn: Who's thriving in disruption, which industries embrace AI, and why others are stuck The hidden cost of tech debt and why most organizations avoid real transformation The power of knowledge graphs, and why they're the key to making AI work at scale  What AI still can't do for us, and the gaps we need to fill with human expertise   Follow Laura on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

We live in a world where people are concerned about social media tracking their data—but at the same time, willingly send their DNA to companies like 23andMe. Why does this happen? What do companies actually do with our data? And how can we, as individuals, become more data-literate to make informed decisions? In this episode, we sit down with Kathy Rondon, author of "We The People: A Playbook for Data Ethics in a Democratic Society," data expert and advocate for data literacy. If you've ever wondered how to take control of your digital footprint, make sense of statistics, or separate fact from fiction in a world full of data, this episode is for you. What You'll Learn: How companies collect and use your data—sometimes in ways you wouldn't expect Why do we trust some organizations with our most personal data while fearing others The power of statistics and how understanding the basics would help everyone better navigate news, research, and even politics   📚 Be sure to check out Kathy's book: "We The People: A Playbook for Data Ethics in a Democratic Society"  Follow Kathy on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

If you were only going to learn a few statistical techniques as an analyst, where should you focus? Josh Starmer, Founder of StatQuest, shares how learning these skills can boost your career. We dive into why linear regression is the bedrock for advanced statistical tests like the t-test, and why understanding Principal Component Analysis (PCA) can give you an edge in working with complex datasets. But it's not just about the math—we also explore how expanding your skill set beyond the numbers can make you a stronger candidate for promotions and new roles. From building a diverse portfolio of skills to positioning yourself effectively in quarterly reviews, we discuss strategies to ensure you stand out in your organization and the broader job market. Whether you're early in your data career or looking to sharpen your expertise, this episode gives you actionable insights to grow both technically and professionally. What You'll Learn: Core statistical methods every analyst should know, including why linear regression is the foundation for advanced analytics  How learning tangential skills like Principal Component Analysis (PCA) can set you apart in the field  Positioning yourself for success in quarterly reviews and career conversations   Be sure to check out Josh's Illustrated Guide to Machine Learning and his YouTube channel! Follow Josh on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Thinking about transitioning into analytics but worried about starting over? Andrew Madson has been in your shoes. Once a compliance executive, Andrew successfully pivoted into analytics and now is a Professor of analytics at five universities. In this episode, we dive deep into what it really takes to make a career shift when you're already successful. Don't miss this conversation packed with real insights for professionals considering a move into analytics! What You'll Learn: How to handle the fear of leaving a high-paying career for something new Why transitioning is different from starting fresh—and how to use your experience as a superpower Bootcamp vs. Master's—what's worth your time and money? The must-have skills and topics when evaluating an analytics education   To hear even more from Andrew, you can check out his YouTube channel Follow Andrew on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

What if your next data presentation felt less like a spreadsheet and more like a blockbuster movie? In this episode, we're joined by Angelica Lo Duca, Researcher at IIT-CNR and a master of transforming numbers into narratives, to explore the intersection of cinematography and data storytelling. Learn how to extract a "hero" from your data, structure your analysis like a compelling story, and tailor your presentations for different audiences to ensure maximum impact. Angelica reveals how the techniques filmmakers use—focusing on key characters, building tension, and delivering climactic resolutions—can be applied to data storytelling. She'll also discuss the role of the data storyteller as a guide and how to strike a balance between clarity and creativity. Whether you're presenting to executives, stakeholders, or teammates, this episode will help you level up your communication skills and make your insights unforgettable. What You'll Learn: How to identify and extract a "hero" from your data to drive a compelling narrative. Cinematic techniques that turn complex analyses into engaging stories. How to tailor your data presentation to resonate with different audiences. The responsibilities and creative power of the data storyteller.   Angelica is the author of Become a Great Storyteller: Learn How You Can Drive Change with Data. Find it here!     Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

In this episode, we'll chat with Carly Taylor, Field CTO of Gaming at Databricks, to explore the fascinating world of data analytics in the gaming industry, where every click, quest, and respawn generates insights that shape the games we love. Carly shares her experience working in gaming to help harness data for better gameplay and smarter monetization. She'll break down what analysts, data scientists, and sales engineers actually do in gaming and how teams turn raw data into real-time decisions. Whether you're a player, a data nerd, or someone who wants to turn both into a career, this episode is your walkthrough guide to data in gaming. What You'll Learn: How gaming companies use data to optimize player experience and business outcomes  What it's like to work in a field engineering or customer-facing analyst role The tools, KPIs, and best practices for success How to break into a data role in gaming and what skills to focus on   Stay updated with Carly's latest by subscribing to her Substack   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

What does it take to turn raw data into actionable insights, especially in high-stakes environments? In this compelling episode, we sit down with Doug Needham, author of Data Structure Synthesis and The Enrichment Game. From his fascinating work updating data virtually during Desert Storm to insights on leveraging third-party data for enterprise decisions, Doug brings a wealth of real-world stories and practical advice to this conversation. You'll learn how to think critically about your data strategy, navigate complex enterprise data ecosystems, and see data as more than just numbers on a screen—it's a resource with untapped potential. Whether you're a data professional, analyst, or someone just starting to explore the world of analytics, this episode is packed with lessons on innovation, efficiency, and making data work smarter, not harder. What You'll Learn: How data enrichment unlocks the full potential of data. The role of data structure synthesis in solving complex enterprise challenges. The realities of working with data in a corporate setting.   Doug is also the author of The Enrichment Game - A Story About Making Data Powerful: find it here!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

If you are interested in a career in Data Science, this one is for you! In this episode with Kimberly Fessel (Dr. Kim Data) & Maven's own Chris Bruehl, you'll learn about the most important skills Data Scientists need, and where you should be focusing your energy. You'll walk away with a solid understanding of the Data Scientist role, core responsibilities, tools of the trade, and a concrete roadmap you can follow to start building skills immediately. What You'll Learn: The technical skills you need for a Data Science career Complementary soft skills that make a difference How to prioritize your learning to make the most of your effort   This session was part of our OPEN CAMPUS week in October, which included 6 days of live expert sessions.   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

What happens when AI becomes your coworker, not your replacement? In this episode, we sit down with Sadie St. Lawrence, founder of HMCI, to explore the rapidly evolving future of work, where AI isn't just a tool, but a teammate. We dig into how blue-collar and white-collar jobs will be shifting as AI and automation move from the periphery into our daily workflows. From analysts to factory floors, from dashboards to shop floors, what will it actually feel like to work alongside intelligent machines? Sadie also shares the deeply personal story of her 18-month journey exiting Women in Data, what she learned in building a global community, and how she's now thinking about the next wave of human + AI collaboration. If you're wondering what your job will look like in 5 years, this one's for you. What You'll Learn: What it really means to work with AI as a teammate How analysts can stay relevant in the age of automation The different futures ahead for blue- vs. white-collar roles How Sadie built, scaled, and thoughtfully exited Women in Data What makes a career resilient in an AI-driven economy   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter