Accelerating ML Training And Delivery With In...

Summary In this episode Jevin Maltais talks about the practical realities of building reliable, product-focused streaming systems with Kafka. Jevin shares lessons from roles at Zapier, Humi, and Clio, where real-time synchronization, customer data unification, and document sync a ...  Show more

Summary In this episode Shravan Gunda, founder and CEO of Kaarvi AI, talks about building an AI-native, agent-driven data platform designed to eliminate the janitorial work that consumes most data teams. He explores Kaarvi’s multi-agent architecture that runs queries across seven ...  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

Modern networked applications generate a lot of data, and every business wants to make the most of that data. Most of the time, that means moving production data through some transformation process to get it ready for the analytics process. But what if you could have in-app analy ...  Show more

I get a lot of emails asking me to talk about graph databases, so I want to start researching them, but I wanted to give you guys the framework of how I think about any databases to defuse any “magic” that might be there.

In this video, I discuss what constrains a datab ...

If the topic of databases is brought up to certain people, their eyes may gloss over. But if that happened, that would be because they just don’t know the awesome power of databases. Data can be valuable but only if it is contextualized, and time is an extremely relevant aspec ...