How can a Snowflake Architect meet this requirement with the LEAST amount of coding?

Files arrive in an external stage every 10 seconds from a proprietary system. The files range in size from 500 K to 3 MB. The data must be accessible by dashboards as soon as it arrives.

How can a Snowflake Architect meet this requirement with the LEAST amount of coding? (Choose two.)
A . Use Snowpipe with auto-ingest.
B . Use a COPY command with a task.
C . Use a materialized view on an external table.
D . Use the COPY INTO command.
E . Use a combination of a task and a stream.

View Answer

Answer: A, C

Explanation:

These two options are the best ways to meet the requirement of loading data from an external stage and making it accessible by dashboards with the least amount of coding.

Snowpipe with auto-ingest is a feature that enables continuous and automated data loading from an external stage into a Snowflake table. Snowpipe uses event notifications from the cloud storage service to detect new or modified files in the stage and triggers a COPY INTO command to load the data into the table. Snowpipe is efficient, scalable, and serverless, meaning it does not require any infrastructure or maintenance from the user. Snowpipe also supports loading data from files of any size, as long as they are in a supported format1.

A materialized view on an external table is a feature that enables creating a pre-computed result set from an external table and storing it in Snowflake. A materialized view can improve the performance and efficiency of querying data from an external table, especially for complex queries or dashboards. A materialized view can also support aggregations, joins, and filters on the external table data. A materialized view on an external table is automatically refreshed when the underlying data in the external stage changes, as long as the AUTO_REFRESH parameter is set to true2.

Reference: Snowpipe Overview | Snowflake Documentation

Materialized Views on External Tables | Snowflake Documentation