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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Account Objects | 8% | - Organizations and accounts structure - Warehouses, databases, and schemas hierarchy - Resource monitors |
| Topic 2: Cloud Platform Overview & Snowflake Key Concepts | 8% | - Snowflake editions and features - Snowflake architecture layers (storage, compute, services) - Virtual warehouse concepts and credit usage |
| Topic 3: Virtual Warehouses | 15% | - Multi-cluster warehouses - Warehouse creation and configuration - Warehouse monitoring and troubleshooting - Warehouse sizing and scaling - Cache concepts (warehouse, result, metadata) |
| Topic 4: Data Sharing | 12% | - Reader account management - Data listing marketplace - Shares and reader accounts - Private sharing vs. Data Exchange |
| Topic 5: Performance Optimization & Monitoring | 4% | - Resource optimization techniques - Query profiling and performance tuning - Query history and monitoring |
| Topic 6: Security & Access Control | 10% | - Governance best practices - Authorization (roles, privileges) - Masking policies - Authentication (SSO, MFA) - Row-level and column-level security |
| Topic 7: Semi-Structured Data | 10% | - Parsing and flattening semi-structured data - Array and object operations - VARIANT data type |
| Topic 8: Databases, Tables & Views | 18% | - Data manipulation (DML operations) - Clustering and micro-partitions - Table types (permanent, transient, temporary) - Column types and sequences - Views (standard, materialized, secure) - Stored procedures and UDFs |
| Topic 9: Data Loading & Unloading | 15% | - File formats (JSON, CSV, Parquet, AVRO) - Continuous loading with Snowpipe - Data ingestion best practices - Data unloading and staging - Bulk loading with COPY command |
| Topic 10: Time Travel & Cloning | 10% | - UNDROP and historical data access - Time travel concepts and retention - Zero-copy cloning - Fail-safe concepts |
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NEW QUESTION # 512
A user needs to load Snowflake files from a stage that contains data from the past 5 years while using the least amount of operational overhead. The file names follow a specific format, such as files ending in _01.gz.
Which command should be used to load the data from 2024?
Answer: B
Explanation:
The correct answer is B. Use the COPY INTO command using the PATTERN parameter to define the needed files .
The PATTERN parameter in the COPY INTO < table > command allows Snowflake to load only files whose names match a specified regular expression. This is useful when a stage contains many files and the required files can be identified by a naming pattern, such as year or suffix.
Why B is correct:
The user needs to load a subset of staged files from a 5-year collection and wants the least operational overhead. Using PATTERN avoids manually listing files, removing files, or downloading and restaging data.
Example concept:
COPY INTO target_table
FROM @my_stage
PATTERN = ' .*2024.*_01[.]gz ' ;
Why the other options are incorrect:
A). Individually loading files creates more manual work and higher operational overhead.
C). Removing unwanted files is risky and unnecessary. It also changes the staged file set.
D). Downloading files with GET, creating a new stage, and reloading files adds unnecessary operational complexity.
Official Snowflake documentation reference:
Snowflake documentation explains that the PATTERN option in COPY INTO < table > specifies a regular expression pattern used to match staged file names for loading.
Reference: Snowflake Documentation - COPY INTO < table > ; Snowflake Documentation - PATTERN copy option; SnowPro Core Study Guide - Data Loading and Unloading.
NEW QUESTION # 513
If queries start to queue in a multi-cluster virtual warehouse, an additional compute cluster starts immediately under what setting?
Answer: D
Explanation:
In Snowflake, when queries begin to queue in a multi-cluster virtual warehouse, an additional compute cluster starts immediately if the warehouse is set to auto-scale mode.This mode allows Snowflake to automatically add or resume additional clusters as soon as the workload increases, and similarly, shut down or pause the additional clusters when the load decreases
NEW QUESTION # 514
Which stage type can be altered and dropped?
Answer: B
Explanation:
External stages can be altered and dropped in Snowflake. An external stage points to an external location, such as an S3 bucket, where data files are stored. Users can modify the stage's definition or drop it entirely if it's no longer needed. This is in contrast to table stages, which are tied to specific tables and cannot be altered or dropped independently.
References:
[ COF-C03 ] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Stages1
NEW QUESTION # 515
What Snowflake tool can be used to share data and metadata to one or more accounts in Snowflake?
Answer: A
NEW QUESTION # 516
What is the MAXIMUM size limit for a record of a VARIANT data type?
Answer: B
Explanation:
The maximum size limit for a record of a VARIANT data type in Snowflake is 16MB. This allows for storing semi-structured data types like JSON, Avro, ORC, Parquet, or XML within a single VARIANT column.References:Based on general database knowledge as of 2021.
NEW QUESTION # 517
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