COF-C02 LATEST EXAM QUESTION | VCE COF-C02 EXAM

COF-C02 Latest Exam Question | Vce COF-C02 Exam

COF-C02 Latest Exam Question | Vce COF-C02 Exam

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Tags: COF-C02 Latest Exam Question, Vce COF-C02 Exam, COF-C02 Reliable Test Pattern, Latest COF-C02 Test Online, COF-C02 Download

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The candidates can test themselves for the SnowPro Core Certification Exam exam day by attempting the SnowPro Core Certification Exam COF-C02 practice test on the software. There is preparation material available on the COF-C02 Practice Exam software by PrepAwayTest to study for the Snowflake COF-C02 test.

Snowflake COF-C02 exam is a comprehensive exam that covers a range of topics related to Snowflake. COF-C02 exam consists of 90 multiple-choice questions and must be completed within 90 minutes. The questions are designed to test an individual's understanding of Snowflake architecture, data loading and unloading, performance tuning, security, and other related topics. COF-C02 Exam is available in multiple languages, including English, Japanese, and German, making it accessible to a wide range of professionals worldwide.

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Snowflake SnowPro Core Certification Exam Sample Questions (Q775-Q780):

NEW QUESTION # 775
Which statements describe benefits of Snowflake's separation of compute and storage? (Select TWO).

  • A. Storage volume growth and compute usage growth can be tightly coupled.
  • B. The separation ensures consistent data encryption across all virtual data warehouses.
  • C. The separation allows independent scaling of computing resources.
  • D. Compute can be scaled up or down without the requirement to add more storage.
  • E. The separation supports automatic conversion of semi-structured data into structured data for advanced data analysis.

Answer: C,D

Explanation:
Snowflake's architecture allows for the independent scaling of compute resources, meaning you can increase or decrease the computational power as needed without affecting storage. This separation also means that storage can grow independently of compute usage, allowing for more flexible and cost-effective data management.


NEW QUESTION # 776
What can be used to view warehouse usage over time? (Select Two).

  • A. The load HISTORY view
  • B. The billing and usage tab in the Snowflake web Ul
  • C. The Query history view
  • D. The show warehouses command
  • E. The WAREHOUSE_METERING__HISTORY View

Answer: C,E

Explanation:
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 information about 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


NEW QUESTION # 777
Which type of workload is recommended for Snowpark-optimized virtual warehouses?

  • A. Workloads with ad hoc analytics
  • B. Workloads that are queried with small table scans and selective filters
  • C. Workloads with unpredictable data volumes for each query
  • D. Workloads that have large memory requirements

Answer: D

Explanation:
Snowpark-optimized virtual warehouses in Snowflake are designed to efficiently handle workloads with large memory requirements. Snowpark is a developer framework that allows users to write code in languages like Scala, Java, and Python to process data in Snowflake. Given the nature of these programming languages and the types of data processing tasks they are typically used for, having a virtual warehouse that can efficiently manage large memory-intensive operations is crucial.
* Understanding Snowpark-Optimized Virtual Warehouses:
* Snowpark allows developers to build complex data pipelines and applications within Snowflake using familiar programming languages.
* These virtual warehouses are optimized to handle the execution of Snowpark workloads, which often involve large datasets and memory-intensive operations.
* Large Memory Requirements:
* Workloads with large memory requirements include data transformations, machine learning model training, and advanced analytics.
* These operations often need to process significant amounts of data in memory to perform efficiently.
* Snowpark-optimized virtual warehouses are configured to provide the necessary memory resources to support these tasks, ensuring optimal performance and scalability.
* Other Considerations:
* While Snowpark can handle other types of workloads, its optimization for large memory tasks makes it particularly suitable for scenarios where data processing needs to be done in-memory.
* Snowflake's ability to scale compute resources dynamically also plays a role in efficiently managing large memory workloads, ensuring that performance is maintained even as data volumes grow.
References:
* Snowflake Documentation: Introduction to Snowpark
* Snowflake Documentation: Virtual Warehouses


NEW QUESTION # 778
Select the different types of Internal Stages: (Choose three.)

  • A. User Stage
  • B. Schema Stage
  • C. Table Stage
  • D. Named Stage

Answer: A,C,D


NEW QUESTION # 779
A Snowflake user has two tables that contain numeric values and is trying to find out which values are present in both tables. Which set operator should be used?

  • A. UNION
  • B. MINUS
  • C. MFRCK
  • D. INTERSECT

Answer: D

Explanation:
To find out which numeric values are present in both tables, the INTERSECT set operator should be used. This operator returns rows from one query's result set which also appear in another query's result set, effectively finding the common elements between the two tables45.


NEW QUESTION # 780
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