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| Section | Weight | Objectives |
|---|---|---|
| Data Loading & Unloading | 15% | - Bulk loading with COPY command - File formats (JSON, CSV, Parquet, AVRO) - Data ingestion best practices - Continuous loading with Snowpipe - Data unloading and staging |
| Account Objects | 8% | - Warehouses, databases, and schemas hierarchy - Resource monitors - Organizations and accounts structure |
| Virtual Warehouses | 15% | - Warehouse sizing and scaling - Cache concepts (warehouse, result, metadata) - Warehouse creation and configuration - Warehouse monitoring and troubleshooting - Multi-cluster warehouses |
| Time Travel & Cloning | 10% | - UNDROP and historical data access - Time travel concepts and retention - Zero-copy cloning - Fail-safe concepts |
| Data Sharing | 12% | - Reader account management - Private sharing vs. Data Exchange - Shares and reader accounts - Data listing marketplace |
| Performance Optimization & Monitoring | 4% | - Query profiling and performance tuning - Resource optimization techniques - Query history and monitoring |
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake architecture layers (storage, compute, services) - Snowflake editions and features - Virtual warehouse concepts and credit usage |
| Security & Access Control | 10% | - Authorization (roles, privileges) - Row-level and column-level security - Masking policies - Authentication (SSO, MFA) - Governance best practices |
| Semi-Structured Data | 10% | - Array and object operations - VARIANT data type - Parsing and flattening semi-structured data |
| Databases, Tables & Views | 18% | - Column types and sequences - Table types (permanent, transient, temporary) - Clustering and micro-partitions - Data manipulation (DML operations) - Stored procedures and UDFs - Views (standard, materialized, secure) |
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NEW QUESTION # 489
Which of the following is a valid source for an external stage when the Snowflake account is located on Microsoft Azure?
Answer: A
Explanation:
In Snowflake, when the account is located on Microsoft Azure, a valid source for an external stage can be an Azure container or a folder path within an Azure container. This includes Azure Blob storage which is accessible via theazure://endpoint. A Windows server file share on Azure, if configured properly, can be a valid source for staging data files for Snowflake.Options A, B, and C are not supported as direct sources for an external stage in Snowflake on Azure12.References:[COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 490
A company needs to read multiple terabytes of data for an initial load as part of a Snowflake migration. The company can control the number and size of CSV extract files.
How does Snowflake recommend maximizing the load performance?
Answer: D
Explanation:
Snowflake's documentation recommends producing the largest files possible for data loading, as larger files reduce the number of files to process and the overhead associated with handling many small files. Thisapproach can maximize the load performance by leveraging Snowflake's ability to ingest large files efficiently1. References: [ COF-C03 ] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 491
How should a user enable Search Optimization Service?
Answer: A
Explanation:
Search Optimization Service is enabled on a table using ALTER TABLE ... ADD SEARCH OPTIMIZATION.
Example:
ALTER TABLE sales ADD SEARCH OPTIMIZATION;
It is not enabled on a warehouse.
Reference: Snowflake Documentation - Enabling Search Optimization Service; ALTER TABLE ... ADD SEARCH OPTIMIZATION.
==
NEW QUESTION # 492
What is an advantage of using an explain plan instead of the query profiler to evaluate the performance of a query?
Answer: C
Explanation:
An explain plan is beneficial because it allows for the evaluation of how a query will be processed without the need to actually execute the query.This can help in understanding the query's performance implications and potential bottlenecks without consuming resources that would be used if the query were run
NEW QUESTION # 493
Which Snowflake data types can be used to build nested hierarchical data? (Select TWO)
Answer: A,E
Explanation:
The Snowflake data types that can be used to build nested hierarchical data are OBJECT and VARIANT.These data types support the storage and querying of semi-structured data, allowing for the creation of complex, nested data structures
NEW QUESTION # 494
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