Feature Stores Take On The Data In Data Science

November 5th, 2020

With contributors:

Gene Leganza , Chandler Hennig

Summary

Data engineers and data scientists turn to feature stores for rapid model development and deployment. Feature stores remove model silos to improve reuse, refactoring, and governance. Explainability is inherent to contain business impact from bias, data drift, decreasing performance, ethical issues, and errors. Data engineers and machine learning engineers should invest in feature stores to expand model deployments and AI opportunities. Schedule an inquiry for more information.

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