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| Section | Weight | Objectives |
|---|---|---|
| Databases, Tables & Views | 18% | - Clustering and micro-partitions - Table types (permanent, transient, temporary) - Data manipulation (DML operations) - Stored procedures and UDFs - Column types and sequences - Views (standard, materialized, secure) |
| Security & Access Control | 10% | - Masking policies - Governance best practices - Authentication (SSO, MFA) - Authorization (roles, privileges) - Row-level and column-level security |
| Data Loading & Unloading | 15% | - Data ingestion best practices - File formats (JSON, CSV, Parquet, AVRO) - Continuous loading with Snowpipe - Data unloading and staging - Bulk loading with COPY command |
| Time Travel & Cloning | 10% | - Time travel concepts and retention - Fail-safe concepts - UNDROP and historical data access - Zero-copy cloning |
| Data Sharing | 12% | - Private sharing vs. Data Exchange - Data listing marketplace - Reader account management - Shares and reader accounts |
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake editions and features - Virtual warehouse concepts and credit usage - Snowflake architecture layers (storage, compute, services) |
| Account Objects | 8% | - Resource monitors - Organizations and accounts structure - Warehouses, databases, and schemas hierarchy |
| Virtual Warehouses | 15% | - Warehouse creation and configuration - Warehouse monitoring and troubleshooting - Cache concepts (warehouse, result, metadata) - Warehouse sizing and scaling - Multi-cluster warehouses |
| Semi-Structured Data | 10% | - Array and object operations - Parsing and flattening semi-structured data - VARIANT data type |
| Performance Optimization & Monitoring | 4% | - Query profiling and performance tuning - Query history and monitoring - Resource optimization techniques |
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NEW QUESTION # 804
Which function can be used to convert semi-structured data into a relational representation?
Answer: B
NEW QUESTION # 805
Which Query Profile metrics can be used to determine if a query is pruning efficiently?
Answer: B
NEW QUESTION # 806
Which of the following are benefits of micro-partitioning? (Select TWO)
Answer: B,C
Explanation:
Micro-partitions in Snowflake are immutable objects, which means once they are written, they cannot be modified. This immutability supports the use of Time Travel, allowing users to access historical data within a defined period. Additionally, micro-partitions can significantly reduce the amount of I/O from object storage to virtual warehouses. This is because Snowflake's query optimizer can skip over micro-partitions that do not contain relevant data for a query, thus reducing the amount of data that needs to be scanned and transferred.
References: [COF-C02] SnowPro Core Certification Exam Study Guide
https://docs.snowflake.com/en/user-guide/tables-clustering-micropartitions.html
NEW QUESTION # 807
Which of the following Snowflake objects can be shared using a secure share? (Select TWO).
Answer: D,E
Explanation:
Secure sharing in Snowflake allows users to share specific objects with other Snowflake accounts without physically copying the data, thus not consuming additional storage. Tables and Secure User Defined Functions (UDFs) are among the objects that can be shared using this feature. Materialized views, sequences, and procedures are not shareable objects in Snowflake.
References:
[ COF-C03 ] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Secure Data Sharing1
NEW QUESTION # 808
How can a user MINIMIZE Continuous Data Protection costs when using large, high-churn, dimension tables?
Answer: C
Explanation:
To minimize Continuous Data Protection (CDP) costs when dealing with large, high-churn dimension tables in Snowflake, using transient tables is a recommended approach.
Transient Tables: These are designed for data that does not require fail-safe protection. They provide the benefit of reducing costs associated with continuous data protection since they do not have the seven-day Fail-safe period that is mandatory for permanent tables.
Periodic Copying to Permanent Tables: By periodically copying data from transient tables to permanent tables, you can achieve a balance between data protection and cost-efficiency. Permanent tables offer the extended data protection features, including Time Travel and Fail-safe, but these features can be applied selectively rather than continuously, reducing the overall CDP costs.
References:
Snowflake Documentation on Transient Tables
Snowflake Documentation on Time Travel & Fail-safe
NEW QUESTION # 809
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