- (Topic 3)
Which statements reflect key functionalities of a Snowflake Data Exchange? (Choose two.)

1. A. If an account is enrolled with a Data Exchange, it will lose its access to the Snowflake Marketplace.
2. B. A Data Exchange allows groups of accounts to share data privately among the accounts.
3. C. A Data Exchange allows accounts to share data with third, non-Snowflake parties.
4. D. Data Exchange functionality is available by default in accounts using the Enterprise edition or higher.
5. E. The sharing of data in a Data Exchange is bidirectiona
6. F. An account can be a provider for some datasets and a consumer for others.

Correct Answer: BE
A Snowflake Data Exchange allows groups of accounts to share data privately among the accounts (B), and it supports bidirectional sharing, meaning an account can be both a provider and a consumer of data (E). This facilitates secure and governed data collaboration within a selected group3.

- (Topic 6)
What is the MINIMUM size of a table for which Snowflake recommends considering adding a clustering key?

1. A. 1 Kilobyte (KB)
2. B. 1 Megabyte (MB)
3. C. 1 Gigabyte (GB)
4. D. 1 Terabyte (TB)

Correct Answer: D
Snowflake recommends considering adding a clustering key to a table when its size reaches1 Terabyte (TB)or larger. Clustering keys help optimize the storage and query performance by organizing the data in a table based on the specified columns. This is particularly beneficial for large tables where data retrieval can become inefficient without proper clustering.
✑ Why Clustering Keys Are Important:Clustering keys ensure that data stored in Snowflake is physically ordered in a way that aligns with the most frequent accesspatterns, thereby reducing the amount of scanned data during queries and improving performance.
✑ Recommendation Basis:The recommendation for tables of size 1 TB or larger is based on the observation that smaller tables generally do not benefit as much from clustering, given Snowflake's architecture. However, as tables grow in size, the benefits of clustering become more pronounced.
✑ Implementing Clustering Keys:
CREATETABLEmy_table (... ) CLUSTERBY(column1, column2);
✑ uk.co.certification.simulator.questionpool.PList@40668a0f ALTERTABLEmy_table CLUSTERBY(column1, column2);
Reference:For additional information on clustering in Snowflake and recommendations on when to use clustering keys, consult the Snowflake documentation on managing and optimizing data clustering: https://docs.snowflake.com/en/user-guide/tables-clustering- keys.html

- (Topic 4)
Which metadata table will store the storage utilization information even for dropped tables?

1. A. DATABASE_STORAGE_USAGE_HISTORY
2. B. TABLE_STORAGE_METRICS
3. C. STORAGE_DAILY_HISTORY
4. D. STAGE STORAGE USAGE HISTORY

Correct Answer: B
The TABLE_STORAGE_METRICS metadata table stores the storage utilization information, including for tables that have been dropped but are still incurring storage costs2.

- (Topic 3)
A materialized view should be created when which of the following occurs? (Choose two.)

1. A. There is minimal cost associated with running the query.
2. B. The query consumes many compute resources every time it runs.
3. C. The base table gets updated frequently.
4. D. The query is highly optimized and does not consume many compute resources.
5. E. The results of the query do not change often and are used frequently.

Correct Answer: BE
A materialized view is beneficial when the query consumes many compute resources every time it runs (B), and when the results of the query do not change often and are used frequently (E). This is because materialized views store pre-computed data, which can speed up query performance for workloads that are run frequently or are complex

- (Topic 5)
Which use case does the search optimization service support?

1. A. Disjuncts (OR) in join predicates
2. B. LIKE/ILIKE/RLIKE join predicates
3. C. Join predicates on VARIANT columns
4. D. Conjunctions (AND) of multiple equality predicates

Correct Answer: D
The search optimization service in Snowflake supports use cases involving conjunctions (AND) of multiple equality predicates. This service enhances the performance of queries that include multiple equality conditions by utilizing search indexes to quickly filter data without scanning entire tables or partitions. It's particularly beneficial for improving the response times of complex queries that rely on specific data matching across multiple conditions.
References:
✑ Snowflake Documentation: Search Optimization Service