6:00 - Doors & Food
6:30 - Talk 1
7:15 - Talk 2
7:45 - Wrap & Chat
Talk 1: An Opinionated Guide to Building an AWS-hosted Data Platform
Tom LeRoux, VP of Data Engineering and Analytics @ Disney Streaming
These days there are many ways to build a cloud-based data warehouse. While AWS makes it easier to deploy infrastructure, it does not provide a prescriptive way to build out a data and analytics platform that meets the needs of both data producers and data consumers.
In this talk we will dive into particular design biases that helped us choose our data architecture for The Walt Disney Company’s direct-to-consumer video businesses globally, including the ESPN+ premium sports streaming service and Disney+, the upcoming Disney subscription video service. We will dig into the different patterns of streaming and batch data ingestions, and talk about how different types of data is transformed and made available to the organization.
Tom LeRoux is VP of Data Engineering at Disney Streaming Services. Tom joined DSS in July of 2018 and runs the data platform that powers Disney+ and ESPN+. Prior to DSS Tom worked at Goldman Sachs where he led the team that built Goldman's new consumer banking data and analytics platform.
Talk 2: How to Design and Scale Financial Data Models and Interfaces
Presenter: Liwei Mao, Senior Software Engineer @ Button
Building a financial data store can be hard. You have many users of financial data within a company. There's the finance team, who sends out monthly invoices and makes projections, the marketing team, who uses financial data to gauge the efficiency of campaigns, the analytics team, who integrate financial data to provide company KPIs. And lastly, your company's external users, to whom you promised easy and accurate access to the transactions you process for them.
In engineering, we often hear let's have a "single source of truth". It’s easy to mistake that to mean, let’s aim to have a single financial data interface that serves all these users needs!
In this talk, we'll detail why that doesn't work. We'll discuss how to design financial data models and interfaces that flexibly and performantly serve user needs while fulfilling the high accuracy requirements for financial data. Lastly, we'll talk about some strategies for scaling and optimizations.
Liwei Mao is a Senior Software Engineer at Button. She loves designing data products, nerding out over databases, and is a firm believer that good data design removes friction in building products.