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A Tour of Features in the Wild and a Modern Solution to Manage Them

Posted Jan 04, 2022 | Views 881
# Data engineering
# Feature Stores
# Systems and Architecture
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SPEAKER
Mike Del Balso
Mike Del Balso
Mike Del Balso
Co-Founder & CEO @ Tecton

Mike Del Balso is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power GoogleÕs Search Ads business. Previous to that, he worked on Google Maps. He holds a BSc in Electrical and Computer Engineering summa cum laude from the University of Toronto.

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Mike Del Balso is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power GoogleÕs Search Ads business. Previous to that, he worked on Google Maps. He holds a BSc in Electrical and Computer Engineering summa cum laude from the University of Toronto.

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SUMMARY

Mike will kick off the event and present his views on the different types of features commonly used for Operational ML use cases, and solutions to manage them.

Operational ML models rely on several types of features with different characteristics such as serving latencies, feature freshness, data sources, and transformation pipelines. We'll categorize the main feature types that are most frequently encountered in real-world use cases, and discuss the specific challenges of building bespoke pipelines for each type.

We'll present our view on a better approach to managing all common feature types. A feature platform is a system designed to manage the complete lifecycle of features. It decouples feature definitions from feature transformations, providing a higher level of abstraction that simplifies the task of building Operational ML, while using modern data infrastructure and best practice architectural patterns.

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