Wondering how today's data product leaders are designing machine learning and analytics solutions that are useful, usable, and valuable to their businesses? How do the disciplines of UX design, data product management, data science, and analytics dance together to build valuable, usable, and indispensable decision support applications?
One of the biggest challenges of today's leaders is that adoption of analytics and ML solutions by users continues to be low or even non-existent. My name is Brian T. O'Neill, and on Experiencing Data, I offer you a designer's perspective on why simply developing ML models, dashboards, and apps—outputs—aren't enough to drive meaningful user and business outcomes with data.
Through solo episodes and interviews with data product leaders, I explore how teams are integrating product-oriented methodologies and UX design to ensure their data-driven applications will get used in the last mile. After all, you can’t create business value if the humans in the loop won’t use the “solution.” I also feature special episodes on XAI, how ML model explainability and interpretability is tied into design and UX, and why data visualization alone isn’t sufficient to produce human-centered applications and user interfaces.
Whether you work in product at a B2B software company, or you build internal data products for a traditional enterprise, join me as I dig into what's working—and what isn't—when it comes to designing simple, valuable, human-centered data products.
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Past Episodes: Audio and Transcripts
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