Snowflake Master Class 2026 | Core + SQL + API + Snowsight

Register for snowflake and start a free 30-day trial with 400 USD of free usage, choosing standard, enterprise, or business critical editions on Azure or Amazon Web Services.

Navigate the snow site interface for Snowflake, sign in with username and password, explore query building, data loading, virtual warehouses, databases, monitoring, data sharing, and account management with multi-factor authentication.

Understand how a Snowflake virtual warehouse supplies compute resources for query processing. Size determines credits per hour and performance, while auto suspend, auto resume, and per-second billing affect cost.

Understand how Snowflake multi-cluster warehouses scale compute to handle peak user and query load, using auto-scale and maximized modes, while managing credits and when to resize versus add more warehouses.

Learn to load data into Snowflake by connecting to an AWS S3 bucket, creating a stage, and building an external table from a CSV data source.

Revisit snowflake architecture and its three layers: data storage, compute, and cloud service, explain independence and the multi-cluster shared architecture, and emphasize cost optimization through efficient ETL and query tuning.

Explore Snowflake pricing: pay only for compute and storage you use, with decoupled resources, region-based credits, on-demand or capacity storage, and scalable warehouse sizing.

Switch to an account admin role to view usage data in the snow site and examine consumption, storage, data transfer, and credits across warehouses for billing.

Explore Snowflake’s built-in and custom roles, switch roles to see how views change, and learn how the six default roles and role hierarchy govern access.

Explore bulk loading and continuous loading with Snowpipe for Snowflake ingestion, using copy commands and virtual warehouses for batches, and stage-based pipelines with streams, tasks, and external tables for transformation.

Explore stages in Snowflake, comparing external stages for cloud storage loading via create stage with internal stages available by default, and learn about user and table stages and put command.

Learn to create a database, schema, an external stage, and an external table in Snowflake, using a public dataset with csv files and an MD5 key.

Import data into Snowflake and perform simple transformations with the copy command, including column selection, a computed is US flag, and country name extraction via substring.

Learn how to handle copy command errors in Snowflake production, using on_error options to continue, skip files, or abort, and review partial loads and error limits.

Explore Snowflake copy options with validation_mode to validate data before loading, including return errors, return all errors, and enforce_length false, and learn how to test rows without copying.

Learn how to retrieve and analyze errors from a Snowflake copy into operation using validation mode and return underscore errors, and explore in-memory results via result_scan and error rows.

Explore the size_limit option for the copy into table command from external sources. The first file always loads; with multiple files, the limit prevents loading further data once exceeded.

Learn to view load history for a table using the load history view and Copy_history, showing file, table, load time, status, and row counts for the last 14 days.

Create a Snowflake stage on S3, define a json external file format, and load json into a variant column, with partitioning on S3 by state.

Snowflake uses automatic caching to speed repeated queries for up to 24 hours or until data changes, and suggests partitioning and avoiding select star, with same warehouse ETL for caching.

Practice Snowflake caching with a hands-on lab using the store_sales sample data, and learn how query profiles reveal table scans and performance gains through cached results.

Explore how to evaluate and implement clustering in Snowflake using clustering keys, partition counts, and histograms, including testing keys with system$ clustering information and assessing reclustering costs.

Learn how to create an Amazon S3 bucket, configure an IAM role and policy, and upload files, with region selection, ownership, privacy settings, and external ID security.

Learn to access a non-public dataset in Snowflake using a storage integration with S3, create a storage integration object, configure allowed locations, and create a stage to upload parquet data.

Learn how Snowpipe automates data loading via cloud notifications from S3 using Amazon SQS, with four stages: create the stage, test the copy command, create a pipe, configure S3 notifications.

Configure an AWS S3 event notification for the Snowpipe public dataset bucket to trigger on all object create events for csv files, delivering notifications to the linked SQS queue.

Discover how to check a pipe's status with system$pipe_status, list pipes with show pipes, pause with pipe_execution_pause=true (notifications queue to S3 while paused), then resume to enable auto ingestion.