Michael A. O’Neill
Thoughts from two decades building data products, platform products, and AI systems. Mostly about trust, context, and the ways product managers get things wrong before they get them right.
Latest on Product
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One Playback Session, Multiple Truths
Why data quality is a product problem, not an engineering problem. Over two decades, I’ve found myself solving the same problem over and over again. People think they’re asking for better data, but what they really want is data they can trust. They’re not the same. I’ve spent most of my career building data products.
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Time to Write a Spec
What one schema misunderstanding taught me about AI and product management A co-worker reached out to me this week, asking for help explaining the relationship between two attributes. Our understanding was product_type is how the content is available and stream_type is how it was consumed. I knew this was wrong, but it was so plausible
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Real-world big data – Preso for a UC Berkeley course about big data
This is my final presentation for UC Berkeley Extension’s Intro to Big Data course. It contains my perspective on the things that a data analyst, data scientist or data engineer will experience and need to watch out for navigating the data sprawl of a massive big-data environment.
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Kickstarting a data-driven culture: Same meeting, many conversations
I’m Mike O’Neill and I’m a data nerd who uses Azure Data Explorer, or Kusto, every day to glean insights into Azure’s developer and code-to-customers operations. I’ve worked in data-driven organizations for most of the last decade plus, so it’s been a bit of a culture shock to work in an organization that doesn’t have