On this episode, we are joined by Will LaForest, Global Field CTO of Confluent, to discuss the transformative impact of data streaming on businesses and platforms. He explains the shift from traditional monolithic big data models to data streaming systems, moving from data analysis to continuously bringing new data to the same questions, enabling hyper-personalized customer experiences and operational efficiency.

Key Takeaways:

(02:59) Will’s early career sparked a passion for large-scale data systems.

(05:25) Data streaming shifts the paradigm by delivering a constant stream of data to the questions.

(08:23) Data streaming helps decouple data producers and deliver data to the consumers in real time.

(17:05) Real-time data streams are used across multiple industries, including financial services and cybersecurity.

(19:36) Ride-sharing exemplifies the indispensable role of data streaming.

(22:49) Reliability, decoupling and speed are some of the reasons data streaming has taken off.

(27:00) Streaming supports hyper-personalized experiences.

(39:36) Confluent simplifies streaming adoption for businesses of all sizes.

Resources Mentioned:

Will LaForest -

https://www.linkedin.com/in/willlaforest/

Confluent | LinkedIn-

https://www.linkedin.com/company/confluent/

Confluent Platform -

https://www.confluent.io/

“Data Mesh” by Zhamak Dehghani -

https://www.thoughtworks.com/insights/books/data-mesh

Apache Kafka -

https://kafka.apache.org/

Apache Flink -

https://kafka.apache.org/

MongoDB -

https://www.mongodb.com/

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