Feature Store in teradataml | Teradata Package for Python - Feature Store in teradataml - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
December 2024
ft:locale
en-US
ft:lastEdition
2025-01-23
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nvi1706202040305.ditamap
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plt1683835213376.ditaval
dita:id
rkb1531260709148
Product Category
Teradata Vantage

Feature Store, also known as Teradata Enterprise Feature Store or Teradata EFS, is a centralized repository to store and manage the lifecycle of Features that are used in ML models. Along with Features, you can also store the components required for building an ML model, preventing the need to modify the ML pipeline even you modify underlying Features or a Data Source which are used while building the ML model.

Advantages of and topics that detail Feature Store follow:
  • The same Features can be used for multiple ML models.
  • FeatureStore decouples model generation from Feature Engineering. So, Data Scientists can focus on model generation while Data Engineers can focus on Feature Engineering.
  • Since Features are stored and versioned with a name, you can improve the trust and reliability on ML model. This is helpful when you work with ML models containing that include a large number of Features.