Free Snowflake COF-C02 Practice Exam with Questions & Answers | Set: 12

 One of the key features of Snowflake’s architecture is its unique approach to eliminating resource contention through the use of virtual warehouses. This is achieved by separating storage and compute resources, allowing multiple virtual warehouses to operate independently on the same data without affecting each other. This means that different workloads, such as loading data, running queries, or performing complex analytics, can be processed simultaneously without any performance degradation due to resource contention.

Column-level security is a feature that allows fine-grained control over access to specific columns within a table. This is particularly useful for managing sensitive data and ensuring that only authorized users can view or manipulate certain pieces of information. According to my last update, this feature was available in the Enterprise Edition or higher editions of Snowflake.

https://docs.snowflake.com/en/user-guide/intro-summary-loading.html#:~:text=For%20delimited%20files%20(CSV%2C%20TSV,encoding%20to%20use%20for%20loading.

For delimited files (CSV, TSV, etc.), the default character set is UTF-8. To use any other characters sets, you must explicitly specify the encoding to use for loading. For the list of supported character sets, see Supported Character Sets for Delimited Files (in this topic).

 The COPY INTO command in Snowflake can be configured to output data into a single file by setting the MAX_FILE_NUMBER option to 1. This option limits the number of files generated by the command, ensuring that only one file is created regardless of the amount of data being exported.

Provisioning time can vary based on the size of the warehouse. A 4X-Large Warehouse typically has more resources and may take longer to provision compared to a X-Small Warehouse, which has fewer resources and can generally be provisioned more quickly.References: Understanding and viewing Fail-safe | Snowflake Documentation

Assigning the custom role to the SYSADMIN role is considered a best practice because it allows the SYSADMIN role to manage objects created by the custom role. This is important for maintaining proper access control and ensuring that the SYSADMIN can perform necessary administrative tasks on objects created by users with the custom role.

The primary responsibility of Snowflake’s virtual warehouses is to execute queries. Virtual warehouses are one of the key components of Snowflake’s architecture, providing the compute power required to perform data processing tasks such as running SQL queries, performing joins, aggregations, and other data manipulations.

 To view warehouse usage over time, the Query history view and the WAREHOUSE_METERING__HISTORY View can be utilized. The Query history view allows users to monitor the performance of their queries and the load on their warehouses over a specified period1. The WAREHOUSE_METERING__HISTORY View provides detailed informationabout the workload on a warehouse within a specified date range, including average running and queued loads2. References: [COF-C02] SnowPro Core Certification Exam Study Guide

Alation is known for specializing in data catalog solutions and is a partner of Snowflake. Data catalog solutions are essential for organizations to effectively manage their metadata and make it easily accessible and understandable for users, which aligns with the capabilities provided by Alation.

 In the query profiler view, the components that represent areas that can be used to help optimize query performance include ‘Bytes scanned’ and ‘Number of partitions scanned’. ‘Bytes scanned’ indicates the total amount of data the query had to read and is a direct indicator of the query’s efficiency. Reducing the bytes scanned can lead to lower data transfer costs and faster query execution. ‘Number of partitions scanned’ reflects how well the data is clustered; fewer partitions scanned typically means better performance because the system can skip irrelevant data more effectively.

 In Snowflake, a reader account is a type of account that is intended for consuming shared data rather than performing any data management or DDL operations. The CREATE SHARE command is used to share data from your account with another account, which is not a capability provided to reader accounts. Reader accounts are typically restricted from creating shares, as their primary purpose is to read shared data rather than to share it themselves.

Transient tables in Snowflake have a default Time Travel retention period of 1 day, which allows users to access historical data within the last 24 hours. However, transient tables do not have a Fail-safe period. Fail-safe is an additional layer of data protection that retains data beyond the Time Travel period for recovery purposes in case of extreme data loss. Since transient tables are designed for temporary or intermediate workloads with no requirement for long-term durability, they do not include a Fail-safe period by default1.

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.

A VARIANT column in Snowflake can store semi-structured data types. This includes:

B. OBJECT: An object is a collection of key-value pairs in JSON, and a VARIANT column can store this type of data structure.

D. ARRAY: An array is an ordered list of zero or more values, which can be of any variant-supported data type, including objects or other arrays.

The VARIANT data type is specifically designed to handle semi-structured data like JSON, Avro, ORC, Parquet, or XML, allowing for the storage of nested and complex data structures.

https://docs.snowflake.com/en/user-guide/admin-security-privatelink.html

When a virtual warehouse in Snowflake is resized, specifically when it is increased in size, the additional compute resources become immediately available to all running and queued queries. Thismeans that the performance of these queries can improve due to the increased resources. Conversely, when the size of a warehouseis reduced, the compute resources are not removed until they are no longer being used by any current operations1.

Snowflake automatically rotates encryption keys when they are more than 30 days old. Active keys are retired, and new keys are created. This process is part of Snowflake’s comprehensive security measures to ensure data protection and is managed entirely by the Snowflake service without requiring user intervention.

 In Snowflake’s architecture, the Cloud Services layer is responsible for generating the query execution plan. This layer handles all the coordination, optimization, and management tasks, including query parsing, optimization, and compilation into an execution plan that can be processed by the Compute layer.

Network policies in Snowflake can be set at the user level and at the account level2.

 Temporary and transient tables in Snowflake do not have a Fail-safe period. Once the session ends or the tables are dropped, the data is purged and not recoverable1.