Data Engineering simplified with Snowpark for Python on Snowflake

Snowpark brings deeply integrated, DataFrame-style programming to the languages developers like to use – as well as functions to help them expand more data use cases easily. It enables data engineers, data scientists, and developers coding in languages like Python to take advantage of Snowflake’s powerful platform without having to first move data out of Snowflake. During this hands-on session, you’ll learn: Setting up your favorite IDE (e.g. Jupyter, VSCode) for Snowpark Analyzing data and performing data engineering tasks using Snowpark DataFrames Using open-source Python libraries with near-zero maintenance or overhead Deploying ML model training code to Snowflake using Python Stored Procedures Creating and registering Python User-Defined Functions (UDFs) for inference

Dash Desai

Sr Technical Evangelist

Snowflake

Biography:

With experience in big data, data science, and machine learning Dash is able to apply 18+ years of full-stack, hands-on software engineering skills to help build solutions that solve business problems and surface trends that shape markets in new ways than imagined before. As a developer advocate, he is passionate about evaluating new ideas, trends, and helping articulate how technology can address a given business problem. Dash has worked for global enterprises and in agile environments–for tech startups in the Bay Area in varying verticals, such as VoIP, Online Gaming, Digital Health, NoSQL database, and Data Cloud platforms.