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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Snowflake Architecture & Core Concepts | 31% | - Snowsight Interface, Core Platform Features - Databases, Schemas, Objects, Data Types - Cloud Services Layer, Compute Layer, Storage Layer - Virtual Warehouses, Clustering, Caching |
| Topic 2: Data Loading, Unloading & Connectivity | 18% | - Bulk Load, Streaming, Dynamic Tables - Stages, File Formats, COPY INTO, Snowpipe - Unloading Data, Export Options - External Integrations, Connectors, SnowSQL |
| Topic 3: Account Management & Data Governance | 20% | - Governance: Resource Monitors, Data Masking, Row/Column Security - Trust Center, Data Lineage, Compliance - Access Control: RBAC, DAC, Roles, Privileges - Security: Network Policies, MFA, Encryption |
| Topic 4: Data Collaboration & Protection | 10% | - Secure Data Sharing, Listings, Marketplace - Data Protection, Retention, Time Travel, Fail-safe - Data Clean Rooms, Collaboration Features |
| Topic 5: Performance Optimization, Querying & Transformation | 21% | - Materialized Views, Streams, Tasks, Pipelines - Query Processing, Profiling, Optimization - Cortex AI, Notebooks, Apache Iceberg Tables - SQL Transformations, Semi-structured/Unstructured Data |
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NEW QUESTION # 663
At what level is the MIN_DATA_RETENTION_TIME_IN_DAYS parameter set?
Answer: A
Explanation:
The MIN_DATA_RETENTION_TIME_IN_DAYS parameter is set at the account level.This parameter determines the minimum number of days Snowflake retains historical data for Time Travel operations
NEW QUESTION # 664
What does the LATERAL modifier for the FLATTEN function do?
Answer: D
Explanation:
The LATERAL modifier for the FLATTEN function allows joining information outside the object (such as other columns in the source table) with the flattened data, creating a lateral view that correlates with the preceding tables in the FROM clause2345. References: [COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 665
When cloning a schema, which Snowflake object will not be included in the clone?
Answer: D
NEW QUESTION # 666
What are the results of the NULL_COUNT Data Metric Function, or DMF, used to verify?
Answer: B
Explanation:
The correct answer is D. The volume of the data .
The NULL_COUNT Data Metric Function returns the number of NULL values in a column. This type of metric is used to verify data quality by measuring the amount, or volume, of missing values.
Why D is correct:
NULL_COUNT counts how many rows contain NULL in a specified column. Since it produces a count, it is used to evaluate the volume of missing data.
Example concept:
SELECT SNOWFLAKE.CORE.NULL_COUNT(
SELECT column_name FROM my_table
);
This returns the number of NULL values found in the selected column.
Why the other options are incorrect:
A). Accuracy verifies whether data values are correct, but NULL_COUNT only counts missing values.
B). Uniqueness is verified with metrics that check duplicate or distinct values, not NULL_COUNT.
C). Freshness measures how current or recent the data is, not how many nulls exist.
Official Snowflake documentation reference:
Snowflake documentation describes NULL_COUNT as a system Data Metric Function that returns the number of NULL values in a column.
Reference: Snowflake Documentation - Data Metric Functions; Snowflake Documentation - SNOWFLAKE.CORE.NULL_COUNT; SnowPro Core Study Guide - Data Protection and Governance.
==
NEW QUESTION # 667
Which command is used to unload data from a Snowflake database table into one or more files in a Snowflake stage?
Answer: D
Explanation:
The COPY INTO <location> command is used to unload data from a Snowflake database table into one or more files in a Snowflake stage1.
NEW QUESTION # 668
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