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| Section | Weight | Objectives |
|---|---|---|
| Virtual Warehouses | 15% | - Warehouse creation and configuration - Warehouse monitoring and troubleshooting - Warehouse sizing and scaling - Multi-cluster warehouses - Cache concepts (warehouse, result, metadata) |
| Data Sharing | 12% | - Shares and reader accounts - Private sharing vs. Data Exchange - Reader account management - Data listing marketplace |
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake editions and features - Snowflake architecture layers (storage, compute, services) - Virtual warehouse concepts and credit usage |
| Semi-Structured Data | 10% | - Array and object operations - Parsing and flattening semi-structured data - VARIANT data type |
| Account Objects | 8% | - Organizations and accounts structure - Resource monitors - Warehouses, databases, and schemas hierarchy |
| Security & Access Control | 10% | - Authentication (SSO, MFA) - Governance best practices - Row-level and column-level security - Authorization (roles, privileges) - Masking policies |
| Data Loading & Unloading | 15% | - Data unloading and staging - Data ingestion best practices - Continuous loading with Snowpipe - File formats (JSON, CSV, Parquet, AVRO) - Bulk loading with COPY command |
| Databases, Tables & Views | 18% | - Table types (permanent, transient, temporary) - Column types and sequences - Data manipulation (DML operations) - Views (standard, materialized, secure) - Clustering and micro-partitions - Stored procedures and UDFs |
| Performance Optimization & Monitoring | 4% | - Resource optimization techniques - Query history and monitoring - Query profiling and performance tuning |
| Time Travel & Cloning | 10% | - UNDROP and historical data access - Zero-copy cloning - Fail-safe concepts - Time travel concepts and retention |
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NEW QUESTION # 1134
Which Snowflake feature allows a user to track sensitive data for compliance, discovery, protection, and resource usage?
Answer: B
Explanation:
Tags in Snowflake allow users to track sensitive data for compliance, discovery, protection, and resource usage. They enable the categorization and tracking of data, supporting compliance with privacy regulations678. References: [ COF-C03 ] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 1135
Which Snowflake layer is associated with virtual warehouses?
Answer: A
Explanation:
The layer of Snowflake ' s architecture associated with virtual warehouses is the Query Processing layer.
Virtual warehouses in Snowflake are dedicated compute clusters that execute SQL queries against the stored data. This layer is responsible for the entire query execution process, including parsing, optimization, and the actual computation. It operates independently of the storage layer, enabling Snowflake to scale compute and storage resources separately for efficiency and cost-effectiveness.
References:
Snowflake Documentation: Snowflake Architecture
NEW QUESTION # 1136
What column type does a Kafka connector store formatted information in a single column?
Answer: B
Explanation:
The Kafka connector stores formatted information in a single column of type VARIANT.This column type is used to store semi-structured data like JSON or Avro, which allows for flexibility in the data structure
NEW QUESTION # 1137
Cloning is being used to create a development environment. Will storage be impacted when cloned tables are modified in a development environment?
Answer: C
Explanation:
Zero-copy cloning initially shares micro-partitions between the source object and the clone. However, when data is modified in either the original or cloned object, Snowflake creates new micro-partitions for the changed data. Those modified micro-partitions consume additional storage.
Reference: Snowflake Documentation - Zero-copy cloning; Micro-partitions; Storage impact of cloned objects.
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NEW QUESTION # 1138
What is the MINIMUM Snowflake edition required to use a dedicated metadata store?
Answer: D
NEW QUESTION # 1139
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