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---
title: The Snowflake MLOps Series — Part 2: The Feature Store
description: Part 2 of a Snowflake MLOps series demonstrating how to use Snowflake's Feature Store to version and track feature sets alongside models. Using TPC-H data and...
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og:description: Part 2 of a Snowflake MLOps series demonstrating how to use Snowflake's Feature Store to version and track feature sets alongside models. Using TPC-H data and...
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# The Snowflake MLOps Series — Part 2: The Feature Store

**[Infostrux](https://daily.dev/sources/infostrux)** · 13 min read · 0 upvotes · 0 comments

## Summary

Part 2 of a Snowflake MLOps series demonstrating how to use Snowflake's Feature Store to version and track feature sets alongside models. Using TPC-H data and XGBoost held constant, the tutorial shows how swapping feature sets (V1: raw line-level columns vs V2: adding P_RETAILPRICE) dramatically changes model performance (R² 0.86 → 0.9999), proving features matter more than algorithms. Covers creating a Feature Store schema, registering entities and feature views, building a spine DataFrame, generating versioned datasets, and traversing ML Lineage to programmatically answer 'which feature set trained this model?' Also discusses static vs. managed (Dynamic Table) feature views and previews upcoming GitOps-for-features content.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.infostrux.com/the-snowflake-mlops-series-part-2-the-feature-store-67d4b07bad23>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#snowflake](https://daily.dev/tags/snowflake), [#mlops](https://daily.dev/tags/mlops), [#xgboost](https://daily.dev/tags/xgboost)

[View this post on daily.dev](https://daily.dev/posts/the-snowflake-mlops-series-part-2-the-feature-store-bmjf9kupw)

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