Getting Data Into Snowflake

Getting data into Snowflake is the first thing every new project needs, but there are several ways to do it — and picking the wrong one leads to slow loads, messy staging, or pipelines that don't scale. Teams often wire up a one-off load script and then struggle when the data grows or the format changes. This session is for the data engineers who want a clear, repeatable way to land data correctly the first time.

We start by mapping the load paths so you know which to reach for, then build a real ingestion flow: staging files and defining file formats, loading in bulk with COPY INTO, organizing the result into a Bronze, Silver, and Gold medallion structure, and automating ongoing loads with Snowpipe. Everything runs on public sample data, so you can follow along in your own account.

In this Hands-on Lab, we will build an ingestion pipeline live in a SQL notebook inside your own Snowflake account: - Choosing the right load path for your data - Creating stages and file formats, and loading files with COPY INTO - Structuring raw data into a Bronze, Silver, and Gold (medallion) model - Automating continuous loads with Snowpipe

Attendees leave with a working ingestion pattern in their own account — staged files, defined file formats, a batch COPY INTO load, a medallion-structured result, and an automated Snowpipe. They'll have the SQL and the decision framework to choose the right approach for any source they need to load.