Use the Snowflake AI Data Cloud architecture — SnowPro® Core Certification

Official references for this objective

• Snowflake — Snowflake key concepts and architecture | Snowflake Documentation

  Snowflake processes queries using massively parallel processing (MPP) compute clusters, where each node in the cluster stores a portion of the entire data set locally

• Snowflake — Micro-partitions & Data Clustering | Snowflake Documentation

  The smaller the average depth, the better clustered the table is with regards to the specified columns.

• Snowflake — Getting Started on the Data Cloud

  Snowflake automatically joins them together, allowing you to replicate data between accounts, enable secure collaboration across geographic regions

• Snowflake — Snowflake’s Elastic Cloud Services

  Larger accounts with more consistent, sustained workloads may be more suited to a single-tenant cluster configuration where underutilization is less of a concern and we

• Snowflake — Supported cloud regions | Snowflake Documentation

  Snowflake does not move data between accounts, so any data in an account in a region remains in the region unless users explicitly choose to

• Snowflake — Understanding overall cost | Snowflake Documentation

  Usage of the cloud services layer is charged only if the daily consumption of cloud services resources exceeds 10% of the daily warehouse usage.

• Snowflake — Virtual warehouses | Snowflake Documentation

  Snowpark-optimized warehouses are recommended for workloads that have large memory requirements such as ML training use cases.