Meet the Expert: Lenny Rosenfeld on Building a Next-Gen Data Platform at Nasdaq

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Meet the Expert: Lenny Rosenfeld on Building a Next-Gen Data Platform at Nasdaq
ISBN: 0636920517047 | .MP4, AVC, 1920x1080, 30 fps | English, AAC, 2 Ch | 55m | 1.13 GB
Instructor: Lenny Rosenfeld

As data volumes grow exponentially, scaling out gets more expensive, data access grows slower, and building and maintaining a data platform using proprietary technologies and protocols becomes less and less feasible. To meet this challenge, Nasdaq's data customers are increasingly moving to the cloud, so the company needed to develop a future-proof, scalable, and feature-rich platform to meet their user and data demands.

Join us for this edition of Meet the Expert with Lenny Rosenfeld to learn how Nasdaq embraced open source technologies, the cloud, and DevOps culture to build its next-gen data platform. You'll dive into the modern yet proven stack based on open technologies (Kafka and Spark), open file formats (Parquet and Avro), and a venue-agnostic fabric (Kubernetes) that helps the company deploy to any cloud no matter where its customers are. And you'll learn how this was accomplished by only four people-and in under six months. Get the real story, hear what the team learned, and catch a glimpse of the future of enterprise data platforms along the way.

O'Reilly Meet the Expert explores emerging business and technology topics and ideas through a series of one-hour interactive events. You'll engage in a live conversation with experts, sharing your questions and ideas while hearing their unique perspectives, insights, fears, and predictions.

What you'll learn-and how you can apply it

By the end of this live show, you'll better understand:

How Nasdaq built a future-proof, scalable, and feature-rich data platform
How the company chose a modern yet proven stack of open source tools, including Spark, Kafka, Parquet, Avro, and Kubernetes

This Discussion is for you because...

You're interested in building and scaling your data platform using open source tools.
You want to learn tools and best practices for working with lots of data, even with a small team.

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