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| Section | Weight | Objectives |
|---|---|---|
| Databases, Tables & Views | 18% | - Data manipulation (DML operations) - Clustering and micro-partitions - Table types (permanent, transient, temporary) - Views (standard, materialized, secure) - Column types and sequences - Stored procedures and UDFs |
| Data Sharing | 12% | - Reader account management - Private sharing vs. Data Exchange - Shares and reader accounts - Data listing marketplace |
| Security & Access Control | 10% | - Row-level and column-level security - Masking policies - Governance best practices - Authorization (roles, privileges) - Authentication (SSO, MFA) |
| Data Loading & Unloading | 15% | - Bulk loading with COPY command - Continuous loading with Snowpipe - Data unloading and staging - Data ingestion best practices - File formats (JSON, CSV, Parquet, AVRO) |
| Virtual Warehouses | 15% | - Warehouse monitoring and troubleshooting - Warehouse sizing and scaling - Warehouse creation and configuration - Cache concepts (warehouse, result, metadata) - Multi-cluster warehouses |
| Semi-Structured Data | 10% | - Array and object operations - VARIANT data type - Parsing and flattening semi-structured data |
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake editions and features - Snowflake architecture layers (storage, compute, services) - Virtual warehouse concepts and credit usage |
| Account Objects | 8% | - Organizations and accounts structure - Resource monitors - Warehouses, databases, and schemas hierarchy |
| Performance Optimization & Monitoring | 4% | - Query profiling and performance tuning - Resource optimization techniques - Query history and monitoring |
| Time Travel & Cloning | 10% | - UNDROP and historical data access - Zero-copy cloning - Time travel concepts and retention - Fail-safe concepts |
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NEW QUESTION # 711
Which feature of Snowflake's Continuous Data Protection (CDP) has associated costs?
Answer: A
Explanation:
Snowflake's Continuous Data Protection (CDP) features encompass several mechanisms designed to protect data and ensure its availability and recoverability. Among these features, the one that has associated costs is Fail-safe.
Fail-safe is an additional layer of protection that kicks in after the Time Travel period expires. While Time Travel allows users to access historical data within a defined retention period (which can vary from 1 to 90 days depending on the Snowflake edition), Fail-safe provides a further 7 days (for a total of 7 additional days beyond the Time Travel period) during which Snowflake retains the data. This period is primarily intended for Snowflake's internal operations to recover data in the event of extreme scenarios, such as significant operational failures, and is not directly accessible by customers for data recovery purposes.
The associated costs with Fail-safe arise because Snowflake continues to store the data beyond the customer-specified Time Travel period, thereby incurring additional storage costs. It's important to note that while users do not incur direct costs for enabling Fail-safe (as it is an automatic feature of Snowflake), the extended storage of data during this period contributes to overall storage costs.
References:
Snowflake Documentation on Continuous Data Protection: Continuous Data Protection (CDP) Snowflake Documentation on Fail-safe: Understanding Fail-safe
NEW QUESTION # 712
When reviewing a query profile, what is a symptom that a query is too large to fit into the memory?
Answer: D
Explanation:
When a query in Snowflake is too large to fit into the available memory, it will start spilling to remote storage. This is an indication that the memory allocated for the query is insufficient for its execution, and as a result, Snowflake uses remote disk storage to handle the overflow. This spill to remote storage can lead to slower query performance due to the additional I/O operations required.
References:
[ COF-C03 ] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Query Profile1
Snowpro Core Certification Exam Flashcards2
NEW QUESTION # 713
How can a data provider ensure that a data consumer is going to have access to the required objects?
Answer: D
Explanation:
To ensure a data consumer has access to the required objects, a data provider can enable the data sharing feature and validate that the consumer can access the views or tables shared with them.References:Based on general data sharing practices in cloud services as of 2021.
NEW QUESTION # 714
A Snowflake Administrator needs to ensure that sensitive corporate data in Snowflake tables is not visible to end users, but is partially visible to functional managers.
How can this requirement be met?
Answer: B
Explanation:
Dynamic data masking is a feature in Snowflake that allows administrators to define masking policies to protect sensitive data.It enables partial visibility of the data to certain roles, such as functional managers, while hiding it from others, like end users
NEW QUESTION # 715
Which file function provides a URL with access to a file on a stage without the need for authentication and authorization?
Answer: C
Explanation:
The GET_PRESIGNED_URL file function in Snowflake provides a URL with access to a file on a stage without requiring authentication and authorization. This is particularly useful for sharing data files stored in Snowflake stages with external parties securely and conveniently. The presigned URL generated by this function gives temporary access to the file, which expires after a specified duration.
Example usage of GET_PRESIGNED_URL:
SELECT GET_PRESIGNED_URL('<stage_name>', '<file_path>');
This function generates a URL that can be used to directly access a file in the stage, making it easier to share data without compromising security.
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NEW QUESTION # 716
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