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.

• 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!

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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!

• 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

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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.

• 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!

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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.

• 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

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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.

• 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!

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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.

• 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.

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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 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

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As AI agents become more powerful and widely adopted, enterprises face a new challenge: how to build them on a foundation of trustworthy, AI-ready data that includes both structured and unstructured data.

Unstructured data introduces new complexity for organizations already contending with large and growing volumes of data that is often distributed and disconnected, and from more information sources.

In this episode, Stephanie Valarezo, Program Director, Product, from IBM Data Integration, shares how organizations can simplify and scale the integration, access and governance of unstructured and structured data.

Explore how IBM is simplifying the enterprise data stack by empowering teams to integrate structured and unstructured data, using batch, real-time streaming, or replication techniques, while extending governance beyond the data layer to the AI agents themselves.

Whether you're modernizing legacy infrastructure, accelerating agent development, or building robust governance strategies, this session will give you a blueprint to:

• Unlock the value of unstructured data for enterprise-grade AI
• Accelerate data intelligence through built-in observability and governance
• Simplify your tech stack while improving trust and traceability in AI outputs

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The analytics industry is evolving faster than ever, and staying ahead requires more than technical expertise—it takes community building, internal advocacy, and the ability to drive impactful projects.

In this episode, Dustin Schimek, Data Fluency Program Manager at MedStar Health, discusses the state of analytics in 2025.

We explore what analysts are working on today, the importance of internal evangelism, and how to spearhead new projects and get to proof of concept (POC) quickly. Dustin also shares insights on standout traits for analysts and why community is at the heart of analytics success.

If you're looking to thrive in analytics and stay at the forefront of the industry, this show is for you!

• Key trends shaping the analytics industry in 2025

• The role of community building and internal evangelism in driving analytics success

• How to accelerate proof of concept (POC) for new analytics projects

• Common themes that make analysts stand out in today's industry

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Data professionals often excel at technical skills but struggle to connect their work to broader business goals.

In this show, we're joined by Jordan Morrow, Senior VP of Data and AI Transformation at AgileOne and author of Business 101 for the Data Professional, to discuss bridging the gap between data and strategy.

Jordan offers practical advice on developing business acumen, aligning data work with organizational goals, and communicating effectively with stakeholders.

Whether you're a data scientist, analyst, or aspiring leader, this conversation will help you unlock the full potential of your data career.

• The essential business skills every data professional needs

• How to align data projects with organizational goals

• Strategies for effective communication with non-technical stakeholders

• Common pitfalls data professionals face when navigating business challenges—and how to avoid them

• Actionable tips to become a more strategic, business-savvy data professional

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