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| Section | Weight | Objectives |
|---|---|---|
| Performance Concepts & Optimization | 15% | - Data optimization features
|
| Data Loading & Transformation | 20% | - Data ingestion methods
|
| Account Access & Security | 20% | - Authentication & authorization
|
| Data Protection & Data Sharing | 10% | - Secure data sharing
|
| Snowflake Architecture & Cloud Concepts | 25% | - Cloud data platform fundamentals
|
| Data Pipelines & Automation | 10% | - Workflow & automation
|
>> Hot Snowflake COF-C02 Spot Questions <<
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NEW QUESTION # 208
A table, STUDENTS, is created using this command:
An example value for the marks is:
Which query will return all of the students' names and history marks?
Answer: D
NEW QUESTION # 209
Which data types does Snowflake support when querying semi-structured data? (Select TWO)
Answer: A,E
Explanation:
https://docs.snowflake.com/en/user-guide/semistructured-intro.html#label-loading-semi-structured-data A VARIANT stores semi-structured data in Snowflake. It can store a value of any other type, including OBJECT and ARRAY.
The maximum length of a VARIANT is 16 MB.
A Snowflake ARRAY is similar to an array in many other programming languages. An ARRAY contains 0 or more pieces of data. Each element is accessed by specifying its position in the array.
NEW QUESTION # 210
A user has semi-structured data to load into Snowflake but is not sure what types of operations will need to be performed on the dat a. Based on this situation, what type of column does Snowflake recommend be used?
Answer: A
Explanation:
When dealing with semi-structured data in Snowflake, and the specific types of operations to be performed on the data are not yet determined, Snowflake recommends using the VARIANT data type. The VARIANT type is highly flexible and capable of storing data in multiple formats, including JSON, AVRO, BSON, and more, within a single column. This flexibility allows users to perform various operations on the data, including querying and manipulation of nested data structures without predefined schemas.
Reference:
Snowflake Documentation: Semi-structured Data Types
NEW QUESTION # 211
What is one of the characteristics of data shares?
Answer: A
Explanation:
Data sharing in Snowflake allows for live, read-only access to data across different Snowflake accounts without the need to copy or transfer the data. One of the characteristics of data shares is the ability to use secure views. Secure views are used within data shares to restrict the access of shared data, ensuring that consumers can only see the data that the provider intends to share, thereby preserving privacy and security.
References:
* Snowflake Documentation: Understanding Secure Views in Data Sharing
NEW QUESTION # 212
What command is used to export or unload data from Snowflake?
Answer: C
Explanation:
The command used to export or unload data from Snowflake to a stage (such as a file in an S3 bucket, Azure Blob Storage, or Google Cloud Storage) is thePUTcommand. ThePUTcommand is designed to upload data files from a local file system (in the case of SnowSQL or other client) or a virtual warehouse to a specified stage. This functionality is critical for scenarios where data needs to be extracted from Snowflake for use in external systems, backups, or further processing.
The syntax for thePUTcommand follows the structure:PUT file:// < local_file_path > @ < stage_name > , where < local_file_path > specifies the path to the file(s) on the localfile system that you wish to upload, and
< stage_name > specifies the destination stage in Snowflake.
It ' s important to distinguish that thePUTcommand is used for exporting data out of Snowflake, whereas theCOPY INTO < table > command is used for importing data into Snowflake from a stage.
TheGETcommand, on the other hand, is used to download files from a stage to the local file system, essentially the inverse operation of thePUTcommand.
References:
Snowflake Documentation on Loading and Unloading Data: [Loading and Unloading Data](https://docs.
snowflake.com/en/user-guide/data-load
NEW QUESTION # 213
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