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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Loading, Unloading & Connectivity | 18% | - Bulk Load, Streaming, Dynamic Tables - Unloading Data, Export Options - External Integrations, Connectors, SnowSQL - Stages, File Formats, COPY INTO, Snowpipe |
| Topic 2: Account Management & Data Governance | 20% | - Access Control: RBAC, DAC, Roles, Privileges - Trust Center, Data Lineage, Compliance - Security: Network Policies, MFA, Encryption - Governance: Resource Monitors, Data Masking, Row/Column Security |
| Topic 3: Snowflake Architecture & Core Concepts | 31% | - Databases, Schemas, Objects, Data Types - Cloud Services Layer, Compute Layer, Storage Layer - Snowsight Interface, Core Platform Features - Virtual Warehouses, Clustering, Caching |
| Topic 4: Performance Optimization, Querying & Transformation | 21% | - Query Processing, Profiling, Optimization - Materialized Views, Streams, Tasks, Pipelines - SQL Transformations, Semi-structured/Unstructured Data - Cortex AI, Notebooks, Apache Iceberg Tables |
| Topic 5: Data Collaboration & Protection | 10% | - Secure Data Sharing, Listings, Marketplace - Data Protection, Retention, Time Travel, Fail-safe - Data Clean Rooms, Collaboration Features |
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NEW QUESTION # 84
Which Snowflake view is used to support compliance auditing?
Answer: D
Explanation:
The ACCESS_HISTORY view in Snowflake is utilized to support compliance auditing. It provides detailed information on data access within Snowflake, including reads and writes by user queries. This view is essential for regulatory compliance auditing as it offers insights into the usage of tables and columns, and maintains a direct link between the user, the query, and the accessed data1.
References: [ COF-C03 ] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 85
What is a characteristic of materialized views in Snowflake?
Answer: D
Explanation:
One of the characteristics of materialized views in Snowflake is that they allow multiple tables to be joined in the underlying query.This enables the pre-computation of complex queries involving joins, which can significantly improve the performance of subsequent queries that access the materialized view4.References:[COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 86
Which column in the ACCESS_HISTORY view in Snowflake describes access history for a column and provides additional information on how columns have been altered over time?
Answer: D
NEW QUESTION # 87
If a column contains float values that are greater than (15,9) and the values need to be preserved when unloading data, what data file format should be used?
Answer: A
Explanation:
The correct answer is A. JSON .
When unloading floating-point or high-precision numeric values, users must consider whether the target file format can preserve the values as needed. JSON stores values in a textual semi-structured representation and can preserve numeric values without forcing them into a fixed Parquet numeric precision representation.
Why A is correct:
For values that exceed a precision/scale such as (15,9) and must be preserved during unloading, JSON is the safest option among the listed choices because it can represent the values textually in the output.
Why the other options are incorrect:
B). PARQUET has limitations for certain numeric precision/scale representations during unload. Snowflake documentation notes precision-related considerations for Parquet unloads.
C). AVRO is a semi-structured file format, but it is not the best documented answer for preserving float values beyond this precision scenario.
D). ORC is not the best answer for this Snowflake unload precision scenario.
Official Snowflake documentation reference:
Snowflake documentation for unloading data explains that file format choice can affect how numeric values are represented and preserved. JSON is commonly used when preserving semi-structured or text-based representations is required.
Reference: Snowflake Documentation - Unloading data; Snowflake Documentation - File format considerations; SnowPro Core Study Guide - Data Loading and Unloading.
NEW QUESTION # 88
What are two ways to create and manage Data Shares in Snowflake? (Choose two.)
Answer: B,C
Explanation:
In Snowflake, Data Shares can be created and managed in two primary ways:
Via the Snowflake Web Interface (UI): Users can create and manage shares through the graphical interface provided by Snowflake, which allows for a user-friendly experience.
Via SQL commands: Snowflake also allows the creation and management of shares using SQL commands. This method is more suited for users who prefer scripting or need to automate the process.
NEW QUESTION # 89
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