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| Section | Objectives |
|---|---|
| Topic 1: Data Loading and Unloading | - External and internal stages - Bulk data loading using stages and COPY INTO |
| Topic 2: Data Sharing and Protection | - Secure data sharing - Data replication and failover concepts |
| Topic 3: Performance and Optimization | - Warehouse sizing and scaling - Query optimization basics |
| Topic 4: Snowflake Architecture and Platform Concepts | - Virtual warehouses and compute model - Storage and data organization - Snowflake architecture fundamentals |
| Topic 5: Data Transformation and Processing | - SQL operations in Snowflake - Streams and tasks for data pipelines |
| Topic 6: Security and Access Control | - Role-based access control (RBAC) - Authentication and user management |
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NEW QUESTION # 795
Which views are included in the data_sharing_usage schema? (Select TWO).
Answer: A,E
Explanation:
https://docs.snowflake.com/en/sql-reference/data-sharing-usage
NEW QUESTION # 796
What can be used to view warehouse usage over time? (Select Two).
Answer: D,E
Explanation:
To view warehouse usage over time, the Query history view and the
WAREHOUSE_METERING__HISTORY View can be utilized. The Query history view allows users to monitor the performance of their queries and the load on their warehouses over a specified period1. The WAREHOUSE_METERING__HISTORY View provides detailed informationabout the workload on a warehouse within a specified date range, including average running and queued loads2. References: [ COF- C03 ] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 797
Which function returns an integer between 0 and 100 when used to calculate the similarity of two strings?
Answer: D
Explanation:
TheJAROWINKLER_SIMILARITYfunction in Snowflake returns an integer between 0 and 100, indicating the similarity of two strings based on the Jaro-Winkler similarity algorithm. This function is useful for comparing strings and determining how closely they match each other.
Understanding JAROWINKLER_SIMILARITY:The Jaro-Winkler similarity metric is a measure of similarity between two strings. The score is a number between 0 and 100, where 100 indicates an exact match and lower scores indicate less similarity.
Usage Example:To compare two strings and get their similarity score, you can use:
SELECTJAROWINKLER_SIMILARITY( ' string1 ' , ' string2 ' )ASsimilarity_score; Application Scenarios:This function is particularly useful in data cleaning, matching, and deduplication tasks where you need to identify similar but not identical strings, such as names, addresses, or product titles.
Reference:For more detailed information on theJAROWINKLER_SIMILARITYfunction and its usage, refer to the Snowflake documentation on string functions: https://docs.snowflake.com/en/sql-reference/functions
/jarowinkler_similarity.html
NEW QUESTION # 798
A user wants to add additional privileges to the system-defined roles for their virtual warehouse. How does Snowflake recommend they accomplish this?
Answer: B
Explanation:
Snowflake recommends enhancing the granularity and management of privileges by creating and utilizing custom roles. When additional privileges are needed beyond those provided by the system-defined roles for a virtual warehouse or any other resource, these privileges should be granted to a custom role. This approach allows for more precise control over access rights and the ability to tailor permissions to the specific needs of different user groups or applications within the organization, while also maintaining the integrity and security model of system-defined roles.
References:
Snowflake Documentation: Roles and Privileges
NEW QUESTION # 799
Which of the following features are available with the Snowflake Enterprise edition? (Choose two.)
Answer: A,B
Explanation:
The Snowflake Enterprise edition includes database replication and failover for business continuity and disaster recovery, as well as extended time travel capabilities for longer data retention periods1.
NEW QUESTION # 800
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