This week on The Data Stack Show, Ryan Dolley joins Eric and John to discuss his unique journey from playwriting to leading product strategy in the data industry. The conversation explores the evolution of business intelligence (BI), the growing influence of AI on analytics, and the shifting skill sets required for data professionals. Key topics include the challenges of adapting to rapid technological change, the importance of embracing engineering practices in BI, and the need for continuous learning. Listeners will gain insights into how AI is transforming data roles, why storytelling remains central to analytics, practical advice for thriving in a fast-changing industry, and so much more.
Highlights from this week’s conversation include:
- Ryan’s Journey: From Playwriting to Data (1:05)
- Making a Living as a Playwright (3:02)
- Transitioning to BI: Night School and First Data Jobs (4:12)
- Storytelling and Data: The Art of BI (6:22)
- Early BI Work: Data Warehouses and PDF Reports (8:33)
- Moving from Utilities to Consulting (13:03)
- Building vs. Implementing: Product Strategy Lessons (16:37)
- The AI Shift in BI and Analytics (18:41)
- Automation Anxiety: The Human Side of Data Change (22:16)
- The Evolving Role of BI Experts (25:18)
- Adapting to Change: Learning Code and Experimentation (29:34)
- AI and the Future of Embedded Analytics (33:38)
- Capturing Intent: The Value of Modern BI Interfaces (37:03)
- Bridging the Data and Software Engineering Gap (39:13)
- The Historical Divide: Data vs. Software Engineering (43:06)
- Organizational Challenges: Where Does BI Belong? (46:05)
- Reflections on Self-Service BI and Value (48:46)
- If Not Data: Ryan’s Alternate Career Paths (49:04)
- Final Thoughts and Takeaways (50:17)
The Data Stack Show is a weekly podcast powered by RudderStack, customer data infrastructure that enables you to deliver real-time customer event data everywhere it’s needed to power smarter decisions and better customer experiences. Each week, we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
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