Streaming Audio: Apache Kafka® & Real-Time Data

Data Modeling for Apache Kafka – Streams, Topics & More with Dani Traphagen

October 07, 2019 Confluent, original creators of Apache Kafka® Season 1 Episode 59
Data Modeling for Apache Kafka – Streams, Topics & More with Dani Traphagen
Streaming Audio: Apache Kafka® & Real-Time Data
More Info
Streaming Audio: Apache Kafka® & Real-Time Data
Data Modeling for Apache Kafka – Streams, Topics & More with Dani Traphagen
Oct 07, 2019 Season 1 Episode 59
Confluent, original creators of Apache Kafka®

Helping users be successful when it comes to using Apache Kafka® is a large part of Dani Traphagen’s role as a senior systems engineer at Confluent. Whether she’s advising companies on implementing parts of Kafka or rebuilding their systems entirely from the ground up, Dani is passionate about event-driven architecture and the way streaming data provides real-time insights on business activity. 

She explains the concept of a stream, topic, key, and stream-table duality, and how each of these pieces relate to one another. When it comes to data modeling, Dani covers importance business requirements, including the need for a domain model, practicing domain-driven design principles, and bounded context. She also discusses the attributes of data modeling: time, source, key, header, metadata, and payload, in addition to exploring the significance of data governance and lineage and performing joins.

EPISODE LINKS

Show Notes

Helping users be successful when it comes to using Apache Kafka® is a large part of Dani Traphagen’s role as a senior systems engineer at Confluent. Whether she’s advising companies on implementing parts of Kafka or rebuilding their systems entirely from the ground up, Dani is passionate about event-driven architecture and the way streaming data provides real-time insights on business activity. 

She explains the concept of a stream, topic, key, and stream-table duality, and how each of these pieces relate to one another. When it comes to data modeling, Dani covers importance business requirements, including the need for a domain model, practicing domain-driven design principles, and bounded context. She also discusses the attributes of data modeling: time, source, key, header, metadata, and payload, in addition to exploring the significance of data governance and lineage and performing joins.

EPISODE LINKS