Mavens of Data

Dirty data isn't just an annoyance; it's a hidden tax on your entire business. From dashboards no one trusts, to AI models trained on flawed inputs, to analysts spending hours fixing the same problems over and over again, poor data quality quietly drains time, money, and confidence. In this episode of Mavens of Data, we're joined by Susan Walsh (data quality expert and The Classification Guru!) to unpack what "dirty data" actually looks like in the real world. We talk through the most common types of dirty data, the downstream problems they cause across analytics, AI, and operations, and Susan's COAT framework for tackling data quality in a way that actually sticks. This isn't about perfection or endless clean-up projects; it's about building smarter processes, preventing problems at the source, and saving yourself (and your team) countless hours down the line. Whether you're an analyst, data engineer, analytics leader, or just someone tired of fixing the same broken fields every week, this conversation will change how you think about data quality. What You'll Learn: The most common (and most expensive) types of dirty data Why dirty data is a business process problem, not a tooling problem Susan's COAT framework and how to apply it in practice How small design choices (like dropdowns) can prevent massive downstream issues Real-world horror stories and how they could have been avoided   🤝 Follow Susan 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 of Mavens of Data, we sit down with Howard Friedman, author of "Winning with Data Science", educator, and practitioner, who has spent years helping organizations turn messy data problems into measurable business wins. We explore the models and decision frameworks used to identify where data science can create the biggest lift inside an organization, from data infrastructure and modeling to reporting, training, and software validation. If you've ever wondered what effective data science looks like in the real world, this episode is your playbook! What You'll Learn: We'll break down three high-impact, real-world transformations: Site Selection Modeling That Eliminated Costly Mistakes How one company improved its revenue forecasts and stopped expensive cannibalization across its retail locations. Howard will walk through what went wrong, how the right product requirements were defined, and what factors were the turning point in improving the forecasts. Loyalty Program Analytics That Drove Double-Digit Growth 1M+ loyalty members, but the organization wasn't sure how to monetize them. Learn how cross-functional collaboration and analysis led to targeted offers, higher engagement, and the reactivation of 50,000+ dormant accounts. LLM Automation in Healthcare - Cutting Documentation Time in Half Howare will tell us about a machine-learning use case at one healthcare company reduced documentation time by 2.5X while maintaining 97% accuracy, freeing clinicians to focus on patients, not forms. These case studies highlight how data science becomes a profit center, not just a technical function.   🤝 Follow Howard 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

Most organizations are drowning in dashboards, KPIs, and visualizations, but starving for insights. In this episode of Mavens of Data, we'll chat with Brent Dykes, Founder of AnalyticsHero and author of Effective Data Storytelling, to break down one of the biggest misconceptions in analytics: a chart is not a story, and a data point is not an insight. Whether you're a data scientist, business analyst, product manager, or analytics leader, this episode will reshape how you communicate with data. If you've ever wondered why your dashboards aren't driving decisions, this conversation will hit home. What You'll Learn: What actually qualifies as an insight How to distinguish reporting ("the what") from storytelling ("the why") Why answering "so what?" is the key to influence The role AI will play in generating insights and telling stories   🤝 Follow Brent 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

You've landed the role, built a few projects, maybe even launched a dashboard or a model,  but how do you make sure your work gets noticed, adopted, and truly moves the needle? In this live session with Dora Boussias, Founder at DoraB Global, we'll dive into the practical skills that transform you from "the person who built something cool" into a trusted, influential data professional. This is about more than doing good technical work; it's about ensuring your work creates visibility, influence, and long-term career growth. Expect concrete advice, examples, and actionable takeaways you can implement today. What You'll Learn: How to build trust with business stakeholders, and how this is the foundation for influence. Quick wins that help you gain credibility in a new role. The difference between being seen as a strong contributor vs. a strategic partner, and how to make that shift. Collaborative approaches to negotiating for resources, scope, or recognition.   This session was part of our Open Campus event, which included 6 days of live expert sessions.   🤝 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

The future of work is here, and it's powered by AI. But what does that mean for your career? In this episode, Maven Analytics Founder Chris Dutton is diving deep into the future of analytics and what you can do to prepare for the rapidly changing landscape. You'll learn how to leverage AI as a powerful partner, not a competitor, and discover a clear path to building a career that is resilient, adaptable, and ready for the future.   This session was part of our January Jumpstart event, which included 6 days of live expert sessions.   🤝 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

How do we create analytics, machine learning, and AI that truly serve people? In this episode, we'll hear from Thais Cooke about putting ethics, bias awareness, and customer centricity at the heart of every data initiative. You'll leave with fresh insights on how to make analytics and AI sustainable, fair, and customer-focused. What You'll Learn: Building responsible analytics and AI strategies Detecting and mitigating bias in data and models Why creativity, business acumen, and communication skills are becoming even more vital Why companies would benefit if their AI focus were less on replacing people   🤝 Follow Thais 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 data analytics but don't come from a traditional STEM or computer science background? In this episode of Mavens of Data, we'll hear from Monica Kay Royal, a data professional, educator, and career mentor, to unpack how effectively demonstrating transferable skills like curiosity, adaptability, communication, problem-solving, and attention to detail can set you apart in analytics. Come learn how to turn your nontraditional experience into a data career What You'll Learn: The many flavors of data analyst roles — from highly technical-heavy positions to more business-oriented, strategic analyst roles. How to identify and articulate the skills you already have that hiring managers care about most. Why soft skills are becoming even more important as technical tools evolve. How to show confidence in interviews by "putting yourself in the role" when asking questions, and why it works.   🤝 Follow Monica 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

It's been a decade since Cole Nussbaumer Knaflic's Storytelling with Data became essential reading for anyone presenting insights visually. But the principles she teaches are timeless, and more relevant than ever. In this show, we dive into the art and craft of data storytelling through a client "makeover" example: a before-and-after transformation of how data is presented and understood. Cole will share about what it means (and how!) to craft a narrative arc and create visuals that lead your audience on a journey. If you've ever built a dashboard, presented findings, or struggled to make your insights resonate, this episode will inspire you to see your data not just as numbers. What You'll Learn: Why knowing your audience and context upfront changes everything How to choose the right type of graph for your story What not to include on a graph (and why simplicity is important) Using visual contrast and color intentionally to guide attention Cole's newest book Storytelling with Data: Before and After shares 20 client makeovers. You can find it here! 🤝 Follow Cole 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 chat with Julia Bardmesser, a data and digital transformation leader with decades of experience guiding teams and organizations to real business impact and author of "From Data to Dollars". Julia believes that if you want to grow in your career, you can't just focus on the tech. You need to ask: What am I building? How is it solving problems? Do I understand the business well enough to deliver better solutions? Am I articulating my work in a way that earns buy-in? Julia shares what it means to "understand the why," how to connect your work to outcomes, and how to communicate value so your ideas gain traction. Whether you're a data analyst, engineer, or leader, Julia's insights will help you think more strategically about the solutions you design and the career you're building. 🤝 Follow Julia on LinkedIn! You can check out "From Data to Dollars" here: https://a.co/d/3yufPak   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

Many data scientists and analytics professionals master the technical craft; coding, modeling, and optimizing. But making the leap from hands-on contributor to leader requires a whole new set of skills. In this episode, we sit down with Brian Evergreen — global AI strategist and author of Autonomous Transformation — to explore how Fortune 10 AI leaders think differently, and how today's data professionals can start building that same mindset. Brian shares the seven leadership skills that help data experts grow into transformative leaders. If you're a data scientist or analyst wondering what's next for your career, or how to lead with vision, this conversation is for you. What You'll Learn: How technical experts can evolve into strategists and value creators Why systems thinking is a hidden superpower How to shift from optimizing existing processes to creating entirely new value Why storytelling is a leadership skill every data professional needs   🤝 Follow Brian 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

When people think about data work, they often picture analytics pipelines or machine learning models. But two areas that often get overlooked are just as important for broadening your impact: Business acumen — understanding markets, stakeholders, and how to become a trusted advisor. Data products — navigating purchased datasets like Nielsen's Billboard ratings or syndicated consumer data. In this episode, Solomon Kahn will explain both of these worlds. From building trusted relationships to making decisions about buying data and what is available, Solomon will show why the most effective data professionals know the business of data from all different aspects. What You'll Learn: Why business acumen is a critical skill for data professionals (and how to develop it) How to move from being a technical contributor to a trusted advisor How purchased datasets like Nielsen Billboard ratings shape entire industries The economics of data as a product, and how to assess ROI before you buy   🤝 Follow Solomon 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 often, data conversations get stuck in silos: tools, models, or dashboards in isolation. But data only delivers value when the entire ecosystem works together. In this episode, Dylan Anderson, Head of Data Strategy at Profusion, joins us to break down what it really means to think holistically about data. We'll explore how business strategy, organizational design, governance, tech debt, and engineering all connect, and why ignoring these links creates inefficiency and frustration. Dylan also shares how he develops "expert generalists" on his team, building data professionals who can see beyond their technical skills and drive real business outcomes. Whether you're leading a team, looking for your next role, or just trying to elevate your impact, this conversation will help you zoom out and think like a strategist, not just a technologist. What You'll Learn: Why treating data topics in isolation leads to hidden inefficiencies and wasted effort  How to align data strategy with business goals (and avoid "models for models' sake")  Practical ways to assess if a company is taking a holistic approach before you join How to grow as a data professional by becoming an "expert generalist"   🤝 Follow Dylan 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 conversation with Nagim Ashufta, Founder of DRIVA GmbH, we dig into what it really looks like when organizations try to get serious about data. Nagim started his own agency to help companies accelerate their data capabilities, and he's seen the same challenges come up again and again. For those in analytics seeking to understand the realities of a data role, this is a great view into the challenges that organizations face, and how you can be prepared. If you're an analytics professional, this episode will give you a practical look at the landscape, the pitfalls, and the messy-but-important role you play in helping data actually deliver. What You'll Learn: Why data is almost never the first role companies hire for, and what this means The common patterns across organizations that struggle with analytics maturity Why "everyone is a data steward" and what stewardship really means in practice   🤝 Follow Nagim 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 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