What Snowflake features should be leveraged when modeling using Data Vault?
A.
Snowflakes support of multi-table inserts into the data models Data Vault tables
B.
Data needs to be pre-partitioned to obtain a superior data access performance
C.
Scaling up the virtual warehouses will support parallel processing of new source loads
D.
Snowflakes ability to hash keys so that hash key joins can run faster than integer joins
Answer:
c
User Votes:
A 2 votes
50%
B
50%
C 1 votes
50%
D 1 votes
50%
Discussions
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akshatbhatia12
7 months, 1 week ago
Snowflake’s support of multi-table inserts into the data model’s Data Vault tables. Data Vault modeling in Snowflake benefits from multi-table inserts, which allow loading data into multiple tables simultaneously within a single transaction.
This ensures data consistency across the Hub, Link, and Satellite tables. Snowflake’s automatic partition pruning optimizes query performance without the need for manual pre-partitioning.
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Snowflake’s support of multi-table inserts into the data model’s Data Vault tables. Data Vault modeling in Snowflake benefits from multi-table inserts, which allow loading data into multiple tables simultaneously within a single transaction.
This ensures data consistency across the Hub, Link, and Satellite tables. Snowflake’s automatic partition pruning optimizes query performance without the need for manual pre-partitioning.