The Anyscale Snowflake Connector enables easy data transfer between Snowflake clusters and Anyscale-hosted Ray clusters, facilitating machine learning discovery and development within Anyscale while leveraging existing Snowflake data lake capabilities. This connector simplifies the creation of end-to-end machine learning workloads by allowing the entire ML pipeline to be executed within a single Python script. It also enables faster execution of machine learning workloads such as training, tuning, and batch serving jobs due to Ray's highly scalable nature. The connector provides simple access to Snowflake data through SQL queries in Anyscale Workspaces Visual Code or JupyterHub environments, while ensuring data security and governance by directly copying data from Snowflake to Ray clusters. By leveraging the parallel read and write capabilities of Ray datasets, large datasets can be queried and transferred quickly into a Ray dataset distributed across the Ray cluster. This enables Data Scientists and Machine Learning Engineers to develop unified workloads with a single Python script that scales across a Ray cluster, integrating with popular AI and ML libraries such as Hugging Face, XGBoost, LightGBM, PyTorch, and TensorFlow.