Data Engineering Lab

Runnable Snowflake data engineering labs with sample data, step-by-step scripts, and cleanup sections.

Looking for Snowflake AI, ML, and Gen AI labs? See the AI/Data Science Lab.

Articles

• Build Managed Transformations With Dynamic Tables: A runnable lab for creating sample source tables, building dynamic tables, refreshing them, checking results, and monitoring refresh history.
• Control Pipelines With Snowflake Scripting Procedures: A runnable lab for creating a Snowflake Scripting stored procedure that validates staged data, merges clean rows, logs results, and handles errors.
• Create, Schedule, Manage, and Monitor Tasks in Snowflake: A runnable Snowflake task walkthrough with sample data, task syntax, scheduling, task graph management, monitoring queries, and cleanup.
• Load and Unload Data With Snowflake Stages and COPY: A runnable lab for creating sample data, unloading it to an internal stage, loading it back with COPY INTO, validating load history, and cleaning up.
• Measure Warehouse Cost and Query Performance: A lab for creating workload data, running queries, inspecting query history, estimating warehouse cost, and understanding compute sizing tradeoffs.
• Practice Secure Data Sharing, Replication, and Failover: A lab for creating share-ready data, secure views, shares, and the syntax patterns for replication and failover groups.
• Practice Snowpipe and Pipe Operations: A runnable lab for creating a pipe definition, staging sample data, practicing COPY validation, inspecting pipe metadata, and understanding auto-ingest operations.
• Protect Sensitive Data With Masking, Row Access, and Tags: A governance lab with sample customer data, tags, a masking policy, a row access policy, and validation queries for sensitive data protection.
• Query Semi-Structured JSON With VARIANT and FLATTEN: A runnable lab for loading JSON into VARIANT columns, extracting attributes, flattening arrays, and building relational outputs.
• Secure Snowflake Access With Roles and Future Grants: A runnable lab for creating roles, schemas, tables, grants, future grants, and managed access patterns used in Snowflake data engineering.
• Tune Pruning, Clustering, and Search Optimization: A performance lab for creating data, testing selective filters, clustering by access pattern, checking clustering metadata, and recognizing search optimization use cases.

What belongs here

• runnable Snowflake platform labs
• ingestion, transformation, task, dynamic table, and monitoring workflows
• sample data that can be created directly from SQL worksheets