Rethinking Feature Stores, with Willem Pienaar (Tecton, Feast, Gojek) - UDEM April 2021

Feature stores have emerged as a key component in the modern machine learning stack. They solve some of the toughest challenges in data for machine learning, namely feature computation, storage, validation, serving, and reuse.

However, the deployment of feature stores still requires a coordinated effort from multiple teams, comes with a large infrastructural footprint, and leads to integration costs and significant operational overheads. This large investment places feature stores completely out of reach for the average data team. What’s needed is a fundamental redesign of the feature store.

In this talk we will introduce a new light weight feature store framework that allows any data source to be operationalized by declaring them as dependencies to production ML applications, without coupling these applications to environment specific infrastructure. By publishing model-centric logical feature definitions, this framework will allow data scientists to build ML applications that depend on any data source, using their tools of choice, and deploy to their existing production infrastructure.

#featurestore #mlops #machinelearning #tecton
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About Willem Pienaar

Willem Pienaar is a tech lead at Tecton, leading the development of Feast, the open source feature store. Previously he led the ML platform team at Gojek, the South-East Asian decacorn, which supported a wide variety of ML use cases and handles hundreds of millions of orders every month. His main focus areas are building data and ML tooling, allowing organizations to scale machine learning and drive decision making. In a previous life, Willem founded and sold a networking startup.