Snowflake - Build and Architect Data Pipelines Using AWS - Introduction to Partitions and clustering keys

The video tutorial introduces micro partitions and clustering in Snowflake. It explains partitioning as dividing large datasets into smaller chunks for independent manipulation. Snowflake uses micro partitions, automatically handling the process. Metadata in micro partitions aids efficient query processing, stored in the cloud services layer. Clustering optimizes data retrieval by grouping similar data. Clustering keys help sort data, enhancing performance. Pruning avoids unnecessary scanning of micro partitions. Snowflake can automatically cluster data, but manual clustering may be needed for better performance. Practical examples illustrate these concepts.

What is the significance of clustering keys in Snowflake?

How does Snowflake optimize data retrieval through pruning?

What considerations should be made when defining clustering keys for optimal performance?