Scaling the Machine Learning Platform at DoorDash

Featuring Hien Luu

DoorDash’s mission is to grow and empower local economies. DoorDash’s business is a 3-sided marketplace composed of Dashers, consumers, and merchants.

As DoorDash's business grows, it is essential to establish a centralized ML platform to accelerate the ML development process and to power the...

Data Mesh; A principled introduction

Featuring Zhamak Dehghani

Data Mesh is an alternative architecture and organizational structure for managing analytical data. Its objective is enabling access to high quality data for analytical and machine learning use cases - at scale.

In this talk, Zhamak will introduce the principles underpinning Data Mesh and...

Islands in the Stream - What country music can teach us about event driven systems

Featuring Simon Aubury

Event driven systems are all the rage. It's with good reason we're witnessing a transformation with businesses adopting event driven systems. Building systems around an event-driven architecture is powerful pattern for creating awesome data intensive applications.But before we sail away to...

Apache Pulsar and the Streaming Ecosystem

Featuring Matteo Merli

Apache Pulsar is an open-source distributed pub-sub messaging system, developed under the stewardship of the Apache Software Foundation.

This talk will show how its unique architecture enables Pulsar to seamlessly support both streaming and messaging use cases in a single unified platform.

Taming the Long Tail of Industrial ML Applications

Featuring Savin Goyal

Data Science usage at Netflix goes much beyond our eponymous recommendation systems. It touches almost all aspects of our business - from optimizing content delivery and informing buying decisions to fighting fraud. Our unique culture affords our data scientists extraordinary freedom of choice in...

Lessons learned from building ML products

Featuring Mikio Braun

Based on my experience as a researcher, working in ecommerce and independent consultant, I talk about some of the lessons learned what is needed beyond pure ML algorithms to successfully build products with ML.

Foundations of Data Teams

Featuring Jesse Anderson

Successful data projects are built on solid foundations. What happens when we’re misled or unaware of what a solid foundation for data teams means? When a data team is missing or understaffed, the entire project is at risk of failure.

This talk will cover the importance of a solid foundation and...

Building & Operating Autonomous Data Streams

Featuring Sid Anand

The world we live in today is fed by data. From self-driving cars and route planning to fraud prevention to content and network recommendations to ranking and bidding, the world we live in today not only consumes low-latency data streams, it adapts to changing conditions modeled by that data.

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Data Rainbows - select * from cloud;

Featuring Nathan Wallace

Drowning in a lake? Stuck inside a warehouse? See your data in a different light! Postgres Foreign Data Wrappers provide SQL queries to live cloud data - all the structure and much lighter weight. In this session, we'll explore the potential of Data Rainbows for growing cloud environments and...

Assisting design with machine learning in Canva’s editor

Featuring Will Radford

Our team at Canva focuses on building features that make design simple, enjoyable and collaborative for more than 55 million people across the globe. For many who haven’t used design tools, starting with a blank page can be intimidating, which is where Canva’s library of more than 500,000...