Blog

A practical reference covering cost, storage, security, performance, and governance queries for Snowflake platform administrators using ACCOUNT_USAGE views.

Feature engineering transforms raw data into ML-ready inputs. Snowflake provides native SQL functions and Snowpark tools to do this without leaving the warehouse.

Snowflake offers multiple paths for ML workloads: Snowpark ML, Cortex ML functions, and in-database model training. Here is how to choose and implement each approach.

Project Snowwork is Snowflake's autonomous AI platform for knowledge workers. Here is why it matters and what data teams should be watching as it develops.

Oracle GoldenGate enables near real-time CDC from Oracle databases into Snowflake via S3 and Snowpipe. Here is how the pipeline works and when to use it.

Snowflake Postgres and the pg_lake extension let you run OLTP workloads and analytical queries on the same Iceberg data layer — without copying data.

The EU AI Act is now enforcing real obligations. Here is what engineering and data teams need to understand about AI compliance, risk categories, and data governance.

Cortex Code is Snowflake's agentic coding experience, purpose-built for data engineers, analysts, and platform teams working inside the Snowflake ecosystem.