Understanding Snowpark for different workloads

The release of Snowpark transformed Snowflake into a complete data platform designed to support various workloads. Snowpark supports multiple workloads, such as data science and ML, data engineering, and data applications.

Data science and ML

Python is the favorite language for data scientists. Snowpark for Python supports popular libraries and frameworks such as pandas, NumPy, and scikit-learn, making it the ideal framework for data scientists to perform ML development in Snowflake. In addition, data scientists can use the DataFrames API to interact with data inside Snowflake and perform batch training and inference inside Snowflake. Developers can also use Snowpark for feature engineering, ML model inference, and end-to-end ML pipelines. Snowpark also provides a SnowparkML library to support data science and ML in Snowpark.

Data engineering

Data cleansing and ELT workloads are complex, and building a data pipeline with just...