Foundational Data Engineering At Two Sigma

Foundational Data Engineering At Two Sigma

Up next

Holding Kafka Right: Product-Friendly Streaming with TypeStream

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

Text to Data Products: Kaarvi’s End-to-End AI for Ingestion, Quality, and Dashboards

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

Recommended Episodes

IoT, IIoT and Managing Edge Data
The Enterprise AI Show

Brian Gilmore (@BrianMGilmore, Director IoT/Emerging Technology @InfluxDB) talks about Edge and Industrial Edge Computing, as well as application and data challenges at the edge.

SHOW: 634

CLOUD NEWS OF THE WEEK - <a href='http://bit.ly/cloudcast-cnot ...

  Show more

3164: Breaking Data Silos: How Hammerspace is Powering AI Storage and Hybrid Cloud
Tech Talks Daily

As part of the IT Press Tour in Silicon Valley, I had the opportunity to sit down with David Flynn, CEO of Hammerspace, to explore how the company is redefining the future of enterprise data storage.

At a time when AI-driven workloads and hybrid cloud computing are push ...

  Show more

AI is more than GenAI
Practical AI

GenAI is often what people think of when someone mentions AI. However, AI is much more. In this episode, Daniel breaks down a history of developments in data science, machine learning, AI, and GenAI in this episode to give listeners a better mental model. Don’t miss this one if y ...  Show more

#295 How To Get Hired As A Data Or AI Engineer with Deepak Goyal, CEO & Founder at Azurelib Academy
DataFramed

The role of data and AI engineers is more critical than ever. With organizations collecting massive amounts of data, the challenge lies in building efficient data infrastructures that can support AI systems and deliver actionable insights. But what does it take to become a succes ...  Show more