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| Section | Weight | Objectives |
|---|---|---|
| Performance and Monitoring | 20% | - Query performance optimization - Query history and profiling - Clustering keys - Resource monitoring and management |
| Account Management and Security | 25% | - Security and governance management - User management and authentication - Role-Based Access Control (RBAC) - Account management and billing |
| Data Management | 20% | - Database object management - Data loading and unloading - Data sharing and replication - Time Travel and Fail-safe |
| Data Protection and Disaster Recovery | 15% | - Backup and restore procedures - Disaster recovery planning - Data replication - Snowflake Marketplace |
| Virtual Warehouses | 20% | - Warehouse performance optimization - Warehouse sizing and scaling - Resource monitors - Virtual warehouse creation and management |
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NEW QUESTION # 55
Which Snowflake objects can be managed using SCIM integration? (Choose two.)
Answer: A,C
Explanation:
SCIM integration in Snowflake is used to manage users and roles for automated provisioning and de-provisioning from external identity providers.
NEW QUESTION # 56
What information is required from the Identity Provider (IdP) to enable federated authentication in Snowflake? (Choose two.)
Answer: B,E
Explanation:
Federated authentication in Snowflake using SAML requires the Identity Provider's SAML endpoint URL so Snowflake can send authentication requests to the IdP during the login process.
Snowflake also requires the IdP's signing certificate to validate the authenticity and integrity of the SAML assertions returned by the Identity Provider during authentication.
NEW QUESTION # 57
What roles can be used to create network policies within Snowflake accounts? (Choose three.)
Answer: A,E,F
Explanation:
SECURITYADMIN, ACCOUNTADMIN, and ORGADMIN roles can create network policies in Snowflake accounts. These roles have the necessary privileges to manage account-level security policies.
NEW QUESTION # 58
A retailer uses a TRANSACTIONS table (100M rows, 1.2 TB) that has been clustered by the STORE_ID column (varchar(50)). The vast majority of analyses on this table are grouped by STORE_ID to look at store performance.
There are 1000 stores operated by the retailer but most sales come from only 20 stores. The Administrator notes that most queries are currently experiencing poor pruning, with large amounts of bytes processed by even simple queries.
Why is this occurring?
Answer: D
Explanation:
Clustering is effective when data distribution across the clustering key is relatively uniform. In this case, most transactions are concentrated in only 20 of the 1000 stores, leading to skewed data distribution. This imbalance causes poor pruning, since large portions of micro-partitions still need to be scanned, even for queries targeting specific stores.
NEW QUESTION # 59
If the query matches the definition, will Snowflake always dynamically rewrite the query to use a materialized view?
Answer: B
Explanation:
Even if a query matches the definition of a materialized view, the Snowflake optimizer may decide not to rewrite the query to use it. The optimizer evaluates factors such as freshness, cost, and efficiency before choosing whether or not to substitute the materialized view.
NEW QUESTION # 60
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