Free Snowflake COF-C02 Practice Exam with Questions & Answers | Set: 10

 In a CREATE PIPE ... AS COPY ... FROM (....) statement, the supported transformations include filtering data using an optional WHERE clause and omitting columns. The WHERE clause allows for the specification of conditions to filter the data that is being loaded, ensuring only relevant data is inserted into the table. Omitting columns enables the exclusion of certain columns from the data load, which can be useful when the incoming data contains more columns than are needed for the target table.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Simple Transformations During a Load1

The list command in Snowflake is used to validate and display the list of files in a specified stage. When a user has unloaded data to a stage, running the list @file__stage command will show all the files that have been uploaded to that stage, allowing the user to verify the data that was unloaded.

References:

Snowflake Documentation on Stages

SnowPro® Core Certification Study Guide

Snowflake supports two geospatial data types: GEOGRAPHY and GEOMETRY. The GEOGRAPHY data type is used to store geospatial data that models the Earth as a perfect sphere, which is suitable for global geospatial data. This data type follows the WGS 84 standard and is used for storing points, lines, and polygons on the Earth’s surface. The GEOMETRY data type, on the other hand, represents features in a planar (Euclidean, Cartesian) coordinate system and is typically used for local spatial reference systems. Since the question specifically asks about geospatial data, which commonly refers to Earth-related spatial data, the correct answer is GEOGRAPHY3. References: [COF-C02] SnowPro Core Certification Exam Study Guide

Semi-structured

JSON, Parquet

Snowflake supports unloading data in several semi-structured file formats, including Parquet and JSON. These formats allow for efficient storage and querying of semi-structured data, which can be loaded directly into Snowflake tables without requiring a predefined schema12.

https://docs.snowflake.com/en/user-guide/data-unload-prepare.html#:~:text=Supported%20File%20Formats,-The%20following%20file &text=Delimited%20(CSV%2C%20TSV%2C%20etc.)

To monitor updates, such as SCIM API requests sent to Snowflake by the identity provider, an administrator can use the REST EVENT HISTORY feature. This feature allows administrators to query historical data about REST API calls made to Snowflake, including those related to user and role management through SCIM (System for Cross-domain Identity Management).

The REST EVENT HISTORY table function returns information about REST API calls made over a specified period. It is particularly useful for auditing and monitoring purposes, especially when integrating Snowflake with third-party identity providers that use SCIM for automated user provisioning and deprovisioning.

An example query to check for SCIM API requests might look like this:

SELECT * FROM TABLE(information_schema.rest_event_history(date_range_start=>dateadd('hours',-1,current_timestamp()))) WHERE request_type = 'SCIM';

This query returns details on SCIM API requests made in the last hour, including the request type, the identity provider's details, and the outcome of each request.

Granting a user the MODIFY, MONITOR, and OPERATE privileges on all virtual warehouses in Snowflake is equivalent to granting the global MANAGE WAREHOUSES privilege. These privileges collectively provide comprehensive control over virtual warehouses.

MODIFY Privilege:

Allows users to change the configuration of the virtual warehouse.

Includes resizing, suspending, and resuming the warehouse.

MONITOR Privilege:

Allows users to view the status and usage metrics of the virtual warehouse.

Enables monitoring of performance and workload.

OPERATE Privilege:

Grants the ability to start and stop the virtual warehouse.

Includes pausing and resuming operations as needed.

References:

Snowflake Documentation: Warehouse Privileges

Masking policies in Snowflake are designed to protect sensitive information by dynamically hiding or obfuscating data based on the role of the user executing the query. This helps enforce data privacy and security by allowing only authorized users to see sensitive information. Masking policies do not encrypt data but apply rules to limit data visibility, ensuring sensitive data is protected during query execution without altering the underlying data.

When creating a CSV file format in Snowflake and the requirement is to wrap columns by single quotes or double quotes, the FIELD_OPTIONALLY_ENCLOSED_BY parameter should be used in the file format specification. This parameter allows you to define a character (either a single quote or a double quote) that can optionally enclose each field in the CSV file, providing flexibility in handling fields that contain special characters or delimiters as part of their data.

References:

Snowflake Documentation: CSV File Format

The Cloud Services layer in Snowflake is responsible for a wide range of services that facilitate the management and use of Snowflake, including:

D. User authentication: This service handles identity and access management, ensuring that only authorized users can access Snowflake resources.

E. Infrastructure management: This service manages the allocation and scaling of resources to meet user demands, including the management of virtual warehouses, storage, and the orchestration of query execution.

These services are part of Snowflake's fully managed, cloud-based architecture, which abstracts and automates many of the complexities associated with data warehousing.

References:

Snowflake Documentation: Overview of Snowflake Cloud Services

The Fail-safe period for a transient table in Snowflake, regardless of the edition (including Enterprise edition and higher), is 0 days. Fail-safe is a data protection feature that provides additional retention beyond the Time Travel period for recovering data in case of accidental deletion or corruption. However, transient tables are designed for temporary or short-term use and do not benefit from the Fail-safe feature, meaning that once their Time Travel period expires, data cannot be recovered.

References:

Snowflake Documentation: Understanding Fail-safe