How To Bring Agile Practices To Your Data Pro...

Summary In this episode Ragnor Comerford talks about OmniGraph, a lakehouse-native graph storage layer designed around the needs of agentic systems. He explores how graphs are primarily a semantic model for representing the world, rather than just a specialized engine for travers ...  Show more

Summary In this episode Prukalpa Sankar, co-founder of Atlan, talks about what it takes to build a “context flywheel” for AI agents in data-intensive organizations. She explained why model intelligence alone isn’t enough to make AI useful in production, and how real performance d ...  Show more

What if you could build and test your product before the full design is complete, and actually start to learn something about it? What if your integration was not just about managing a bunch of interfaces around suppliers but also about managing your technical risks so that you c ...  Show more

Organizations use their data to make better decisions and build innovative experiences for their customers. With the exponential growth in data, and the rapid pace of innovation in machine learning (ML), there is a growing need to build modern data applications that are agile and ...  Show more

Everyone working in application development deals with the problems addressed by design systems. In this Episode, we discuss with Wade Harkins about the benefits of Design Systems, how to implement them with your team, some of the unexpected hurdles that can arise along the way, ...  Show more

Everyone working in data science and AI knows about Anaconda and has probably “conda” installed something. But how did Anaconda get started and what are they working on now? Peter Wang, CEO of Anaconda and creator of PyData and popular packages like Bokeh and DataShader, joins us ...  Show more