Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk. This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform. You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Discussion on building models on real-time data using Jupyter notebooks and Streambased.