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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Pipelines & Automation | 10% | - Integration & connectivity
|
| Topic 2: Data Loading & Transformation | 20% | - Data ingestion methods
|
| Topic 3: Account Access & Security | 20% | - Authentication & authorization
|
| Topic 4: Performance Concepts & Optimization | 15% | - Data optimization features
|
| Topic 5: Snowflake Architecture & Cloud Concepts | 25% | - Cloud data platform fundamentals
|
| Topic 6: Data Protection & Data Sharing | 10% | - Secure data sharing
|
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NEW QUESTION # 243
Which command is used to lake away staged files from a Snowflake stage after a successful data ingestion?
Answer: D
Explanation:
The REMOVE command is used in Snowflake to delete files from a stage after they have been successfully ingested into Snowflake tables. This command helps manage storage by allowing users to clean up staged files that are no longer needed, ensuring that the stage does not accumulate unnecessary data over time.
Unlike DELETE, DROP, or TRUNCATE commands, which are used for managing data within Snowflake tables or dropping objects, REMOVE specifically targets the management of files in stages.References:
Snowflake Documentation on Stages and File Management
NEW QUESTION # 244
Snowflake provides a mechanism for its customers to override its clustering algorithms.
This method is:
Answer: C
NEW QUESTION # 245
Which setting will help control credit consumption for a virtual warehouse that needs to run in Auto-scale mode?
Answer: A
Explanation:
The correct answer is A. Set the warehouse scaling policy to ECONOMY .
A multi-cluster warehouse can use Auto-scale mode to add or remove clusters based on query concurrency.
To help control credit consumption, Snowflake provides an Economy scaling policy.
Why A is correct:
The ECONOMY scaling policy is more conservative than the STANDARD scaling policy. It starts additional clusters only when Snowflake estimates there is enough query load to keep the new cluster busy for a meaningful amount of time. This helps reduce unnecessary cluster starts and can lower credit usage.
Why the other options are incorrect:
B). Setting MIN_CLUSTER_COUNT = 1 can help avoid running multiple clusters constantly, but it does not specifically control Auto-scale behavior as effectively as the Economy scaling policy.
C). Setting AUTO_SUSPEND = 0 disables automatic suspension, which can increase credit consumption.
D). Setting both minimum and maximum cluster count to 2 forces two clusters and removes Auto-scale flexibility. This can increase cost and does not control consumption efficiently.
Official Snowflake documentation reference:
Snowflake documentation explains that the Economy scaling policy conserves credits by starting additional clusters only when enough query load exists to justify them.
Reference: Snowflake Documentation - Multi-cluster warehouses; Snowflake Documentation - Scaling policy; SnowPro Core Study Guide - Snowflake Account and Resource Management.
NEW QUESTION # 246
While running a query on a virtual warehouse in auto-scale mode, additional clusters are stated immediately if which setting is configured?
Answer: C
NEW QUESTION # 247
What can a user win a reader account do in Snowflake?
Answer: A
Explanation:
In Snowflake, a user within a reader account primarily has read-only access to the shared data. Reader accounts are created to enable third parties or separate business units to access and query data shared with them without allowing them to modify the underlying data. This means a user with a reader account can perform operations like querying shared data to analyze or report on it but cannot load new data, update existing data, or create new shares. This setup is crucial for maintaining data governance and security while enabling data sharing and collaboration.References: Snowflake Documentation on Reader Accounts
NEW QUESTION # 248
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