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Snowflake COF-C02 Practice Test - Questions Answers, Page 62

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What are potential impacts of storing non-native values like dates and timestamps in a variant column in Snowflake?

A.
Faster query performance and increased storage consumption
A.
Faster query performance and increased storage consumption
Answers
B.
Slower query performance and increased storage consumption
B.
Slower query performance and increased storage consumption
Answers
C.
Faster query performance and decreased storage consumption
C.
Faster query performance and decreased storage consumption
Answers
D.
Slower query performance and decreased storage consumption
D.
Slower query performance and decreased storage consumption
Answers
Suggested answer: B

Explanation:

Storing non-native values, such as dates and timestamps, in a VARIANT column in Snowflake can lead to slower query performance and increased storage consumption. VARIANT is a semi-structured data type that allows storing JSON, AVRO, ORC, Parquet, or XML data in a single column. When non-native data types are stored as VARIANT, Snowflake must perform implicit conversion to process these values, which can slow down query execution. Additionally, because the VARIANT data type is designed to accommodate a wide variety of data formats, it often requires more storage space compared to storing data in native, strongly-typed columns that are optimized for specific data types.

The performance impact arises from the need to parse and interpret the semi-structured data on the fly during query execution, as opposed to directly accessing and operating on optimally stored data in its native format. Furthermore, the increased storage consumption is a result of the overhead associated with storing data in a format that is less space-efficient than the native formats optimized for specific types of data.

References:

Snowflake Documentation on Semi-Structured Data: Semi-Structured Data

Which views are included in the data_sharing_usage schema? (Select TWO).

A.
ACCESS_HISTORY
A.
ACCESS_HISTORY
Answers
B.
DATA_TRANSFER_HISTORY
B.
DATA_TRANSFER_HISTORY
Answers
C.
WAREHOUSE_METERING_HISTORY
C.
WAREHOUSE_METERING_HISTORY
Answers
D.
MONETIZED_USAGE_DAILY
D.
MONETIZED_USAGE_DAILY
Answers
E.
LISTING TELEMETRY DAILY
E.
LISTING TELEMETRY DAILY
Answers
Suggested answer: D, E

Explanation:

https://docs.snowflake.com/en/sql-reference/data-sharing-usage

How does the Access_History view enhance overall data governance pertaining to read and write operations? (Select TWO).

A.
Shows how the accessed data was moved from the source lo the target objects
A.
Shows how the accessed data was moved from the source lo the target objects
Answers
B.
Provides a unified picture of what data was accessed and when it was accessed
B.
Provides a unified picture of what data was accessed and when it was accessed
Answers
C.
Protects sensitive data from unauthorized access while allowing authorized users to access it at query runtime
C.
Protects sensitive data from unauthorized access while allowing authorized users to access it at query runtime
Answers
D.
Identifies columns with personal information and tags them so masking policies can be applied to protect sensitive data
D.
Identifies columns with personal information and tags them so masking policies can be applied to protect sensitive data
Answers
E.
Determines whether a given row in a table can be accessed by the user by filtering the data based on a given policy
E.
Determines whether a given row in a table can be accessed by the user by filtering the data based on a given policy
Answers
Suggested answer: B, E

Explanation:

The ACCESS_HISTORY view in Snowflake is a powerful tool for enhancing data governance, especially concerning monitoring and auditing data access patterns for both read and write operations. The key ways in which ACCESS_HISTORY enhances overall data governance are:

B . Provides a unified picture of what data was accessed and when it was accessed: This view logs details about query executions, including the objects (tables, views) accessed and the timestamps of these accesses. It's instrumental in auditing and compliance scenarios, where understanding the access patterns to sensitive data is critical.

E . Determines whether a given row in a table can be accessed by the user by filtering the data based on a given policy: While this option is a bit of a misinterpretation of what ACCESS_HISTORY directly offers, it indirectly supports data governance by providing the information necessary to analyze access patterns. This analysis can then inform policy decisions, such as implementing Row-Level Security (RLS) to restrict access to specific rows based on user roles or attributes.

ACCESS_HISTORY does not automatically apply data masking or tag columns with personal information. However, the insights derived from analyzing ACCESS_HISTORY can be used to identify sensitive data and inform the application of masking policies or other security measures.

References:

Snowflake Documentation on ACCESS_HISTORY: Access History

Which Snowflake feature or tool helps troubleshoot issues in SQL query expressions that commonly cause performance bottlenecks?

A.
Persisted query results
A.
Persisted query results
Answers
B.
QUERY_HISTORY View
B.
QUERY_HISTORY View
Answers
C.
Query acceleration service
C.
Query acceleration service
Answers
D.
Query Profile
D.
Query Profile
Answers
Suggested answer: D

Explanation:

The Snowflake feature that helps troubleshoot issues in SQL query expressions and commonly identify performance bottlenecks is the Query Profile. The Query Profile provides a detailed breakdown of a query's execution plan, including each operation's time and resources consumed. It visualizes the steps involved in the query execution, highlighting areas that may be causing inefficiencies, such as full table scans, large joins, or operations that could benefit from optimization.

By examining the Query Profile, developers and database administrators can identify and troubleshoot performance issues, optimize query structures, and make informed decisions about potential schema or indexing changes to improve performance.

References:

Snowflake Documentation on Query Profile: Using the Query Profile

Which function returns the URL of a stage using the stage name as the input?

A.
BUILD_STAGE_FILE_URL
A.
BUILD_STAGE_FILE_URL
Answers
B.
BUILD_SCOPED_FILE_URL
B.
BUILD_SCOPED_FILE_URL
Answers
C.
GET_PRESIGNED_URL
C.
GET_PRESIGNED_URL
Answers
D.
GET STAGE LOCATION
D.
GET STAGE LOCATION
Answers
Suggested answer: C

Explanation:

The function in Snowflake that returns the URL of a stage using the stage name as the input is C. GET_PRESIGNED_URL. This function generates a pre-signed URL for a specific file in a stage, enabling secure, temporary access to that file without requiring Snowflake credentials. While the function is primarily used for accessing files in external stages, such as Amazon S3 buckets, it is instrumental in scenarios requiring direct, secure file access for a limited time.

It's important to note that as of my last update, Snowflake's documentation does not specifically list a function named GET_PRESIGNED_URL for directly obtaining a stage's URL by its name. The description aligns closely with functionality available in cloud storage services (e.g., AWS S3's presigned URLs) which can be used in conjunction with Snowflake stages for secure, temporary access to files. For direct interaction with stages and their files, Snowflake offers various functions and commands, but the exact match for generating a presigned URL through a simple function call may vary or require leveraging external cloud services APIs in addition to Snowflake's capabilities.

References:

Snowflake Documentation and cloud services (AWS, Azure, GCP) documentation on presigned URLs and stage interactions.

When does a materialized view get suspended in Snowflake?

A.
When a column is added to the base table
A.
When a column is added to the base table
Answers
B.
When a column is dropped from the base table
B.
When a column is dropped from the base table
Answers
C.
When a DML operation is run on the base table
C.
When a DML operation is run on the base table
Answers
D.
When the base table is reclustered
D.
When the base table is reclustered
Answers
Suggested answer: B

Explanation:

A materialized view in Snowflake gets suspended when structural changes that could impact the view's integrity are made to the base table, such as B. When a column is dropped from the base table. Dropping a column from the base table on which a materialized view is defined can invalidate the view's data, as the view might rely on the column that is being removed. To maintain data consistency and prevent the materialized view from serving stale or incorrect data, Snowflake automatically suspends the materialized view.

Upon suspension, the materialized view does not reflect changes to the base table until it is refreshed or re-created. This ensures that only accurate and current data is presented to users querying the materialized view.

References:

Snowflake Documentation on Materialized Views: Materialized Views

What does a table with a clustering depth of 1 mean in Snowflake?

A.
The table has only 1 micro-partition.
A.
The table has only 1 micro-partition.
Answers
B.
The table has 1 overlapping micro-partition.
B.
The table has 1 overlapping micro-partition.
Answers
C.
The table has no overlapping micro-partitions.
C.
The table has no overlapping micro-partitions.
Answers
D.
The table has no micro-partitions.
D.
The table has no micro-partitions.
Answers
Suggested answer: C

Explanation:

In Snowflake, a table's clustering depth indicates the degree of micro-partition overlap based on the clustering keys defined for the table. A clustering depth of 1 implies that the table has no overlapping micro-partitions. This is an optimal scenario, indicating that the table's data is well-clustered according to the specified clustering keys. Well-clustered data can lead to more efficient query performance, as it reduces the amount of data scanned during query execution and improves the effectiveness of data pruning.

References:

Snowflake Documentation on Clustering: Understanding Clustering Depth

Which Snowflake object contains all the information required to share a database?

A.
Private listing
A.
Private listing
Answers
B.
Secure view
B.
Secure view
Answers
C.
Sequence
C.
Sequence
Answers
D.
Share
D.
Share
Answers
Suggested answer: D

Explanation:

In Snowflake, a Share is the object that contains all the information required to share a database with other Snowflake accounts. Shares are used to securely share data stored in Snowflake tables and views, enabling data providers to grant data consumers access to their datasets without duplicating data. When a database is shared, it can include one or more schemas, and each schema can contain tables, views, or both.

References:

Snowflake Documentation on Shares: Shares

Based on Snowflake recommendations, when creating a hierarchy of custom roles, the top-most custom role should be assigned to which role?

A.
ACCOUNTADMIN
A.
ACCOUNTADMIN
Answers
B.
SECURITYADMIN
B.
SECURITYADMIN
Answers
C.
SYSADMIN
C.
SYSADMIN
Answers
D.
USERADMIN
D.
USERADMIN
Answers
Suggested answer: A

Explanation:

Based on Snowflake recommendations, when creating a hierarchy of custom roles, the top-most custom role should ideally be granted to the ACCOUNTADMIN role. This recommendation stems from the best practices for implementing a least privilege access control model, ensuring that only the necessary permissions are granted at each level of the role hierarchy. The ACCOUNTADMIN role has the highest level of privileges in Snowflake, including the ability to manage all aspects of the Snowflake account. By assigning the top-most custom role to ACCOUNTADMIN, you ensure that the administration of role hierarchies and the assignment of roles remain under the control of users with the highest level of oversight and responsibility within the Snowflake environment.

References:

Snowflake Documentation on Access Control: Managing Access Control

Which Snowflake table type is only visible to the user who creates it, can have the same name as permanent tables in the same schema, and is dropped at the end of the session?

A.
Temporary
A.
Temporary
Answers
B.
Local
B.
Local
Answers
C.
User
C.
User
Answers
D.
Transient
D.
Transient
Answers
Suggested answer: A

Explanation:

In Snowflake, a Temporary table is a type of table that is only visible to the user who creates it, can have the same name as permanent tables in the same schema, and is automatically dropped at the end of the session in which it was created. Temporary tables are designed for transient data processing needs, where data is needed for the duration of a specific task or session but not beyond. Since they are automatically cleaned up at the end of the session, they help manage storage usage efficiently and ensure that sensitive data is not inadvertently persisted.

References:

Snowflake Documentation on Temporary Tables: Temporary Tables

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