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How to Do Agentic Data Analysis

Monday, July 20, 11 AM ET

Key Takeaways

  • Learn what AI can and can’t do in data analysis — where to automate, where it works as a copilot, and where human judgment is essential.
  • Explore the tech stack behind agentic data analytics and get hands-on building agentic workflows.
  • Understand how to “think meta” for better AI-assisted problem solving, and what agentic AI means for data analyst roles and careers.

Your Presenter(s)

Dave Wentzel headshot

Dave Wentzel

Technical Architect at Microsoft Innovation Hub

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Dave has been doing analytics since the 1990s, and frankly very little of it is relevant to how we do analytics in 2026.  When I hire people I don’t look for people with a lot of experience – they tend to also have a ton of baggage that I do NOT want.  What I want is a person with critical thinking skills, intellectual curiosity, and the ability to learn the latest technology quickly.  Move fast - break things.

Why this matters

The boundaries of what AI can do in data analysis are shifting fast—but so is the confusion about where automation helps and where it falls short. For data analysts and scientists, understanding the real capabilities and limits of agentic AI is now a core professional skill. Knowing when to automate, when to collaborate with AI as a copilot, and when human judgment is irreplaceable is what separates effective practitioners from those left behind.

In this code-along webinar, Dave Wentzel, Technical Evangelist at Microsoft’s Office of the CTO, will walk you through how to approach agentic data analysis in practice. You’ll explore the tech stack powering agentic analytics, learn how to “think meta” for sharper AI-assisted problem solving, and understand how these shifts are reshaping data analysis roles and careers.

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