In this quickstart, you will learn how to build the key components of a feature store workflow, including entities, feature views, and datasets. Entities represent the real-world objects or concepts that your features describe, such as customers or products. Feature views provide a structured way to define and store these features, allowing for consistent and efficient retrieval. Finally, datasets are collections of features that are prepared for model training or inference. By the end of this quickstart, you’ll have a solid understanding of how to create and manage these components within the Snowflake Feature Store, setting the foundation for building robust and scalable machine learning pipelines.
For prerequisites, environment setup, step-by-step guide and instructions, please refer to the QuickStart Guide.