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Snowflake ADA-C02 Exam Syllabus Topics:

Section	Objectives
Data Protection and Recovery	- Backup and recovery mechanisms 1. Cloning and data recovery strategies 2. Time Travel and Fail-safe concepts
Snowflake Architecture and Virtual Warehouses	- Snowflake architecture concepts 1. Virtual warehouse usage and scaling 2. Separation of storage and compute
Data Loading and Unloading	- Bulk and continuous data ingestion 1. COPY INTO operations 2. Stages and file formats
Security and Access Control	- Authentication and authorization 1. Network policies and secure access 2. Role-based access control (RBAC)
Account and Resource Administration	- Account configuration and management 1. Resource monitors and governance basics 2. Users, roles, and permissions
Performance and Monitoring	- Performance tuning and optimization 1. Query performance analysis 2. Warehouse sizing and scaling strategies

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Snowflake SnowPro Advanced Administrator ADA-C02 Sample Questions (Q22-Q27):

NEW QUESTION # 22
What are benefits of creating and maintaining resource monitors in Snowflake? (Choose three.)

A. Resource monitors can be applied to more than one virtual warehouse.
B. The cost of running a resource monitor is only 10% of a credit, per day of operation.
C. Multiple triggers can be configured across various virtual warehouse thresholds.
D. Resource monitor governance is tightly controlled and monitors can only be created by the ACCOUNTADMIN role or users with the CREATE MONITOR privilege.
E. Multiple resource monitors can be applied to a single virtual warehouse.
F. Resource monitors add no additional load to virtual warehouse compute.

Answer: A,C,E

Explanation:
Multiple resource monitors can be assigned to a single virtual warehouse for granular credit control.
Resource monitors support multiple triggers at different usage thresholds.
A single resource monitor can govern multiple virtual warehouses.

NEW QUESTION # 23
An Administrator loads data into a staging table every day. Once loaded, users from several different departments perform transformations on the data and load it into different production tables.
How should the staging table be created and used to MINIMIZE storage costs and MAXIMIZE performance?

A. Create it as a permanent table with a retention time of 0 days.
B. Create it as a temporary table with a retention time of 0 days.
C. Create it as a transient table with a retention time of 0 days.
D. Create it as an external table, which will not incur Time Travel costs.

Answer: C

Explanation:
A transient table is best suited for staging because it avoids long-term storage costs by not maintaining Fail-safe and can have Time Travel retention set to 0 days. This minimizes storage costs while still providing performance comparable to permanent tables, making it the optimal choice for daily staging data.

NEW QUESTION # 24
A Snowflake customer is experiencing higher costs than anticipated while migrating their data warehouse workloads from on-premises to Snowflake. The migration workloads have been deployed on a single warehouse and are characterized by a large number of small INSERTS rather than bulk loading of large extracts. That single warehouse has been configured as a single cluster, 2XL because there are many parallel INSERTS that are scheduled during nightly loads.
How can the Administrator reduce the costs, while minimizing the overall load times, for migrating data warehouse history?

A. The INSERTS should be converted to several tables to avoid contention on large tables that slows down query processing.
B. There should be another 2XL warehouse deployed to handle a portion of the load queries.
C. The 2XL warehouse should be changed to 4XL to increase the number of threads available for parallel load queries.
D. The warehouse should be kept as a SMALL or XSMALL and configured as a multi-cluster warehouse to handle the parallel load queries.

Answer: D

Explanation:
For many small, parallel INSERTS, using a multi-cluster warehouse with smaller size (SMALL or XSMALL) allows more concurrent queries to run efficiently and reduces costs compared to a single large warehouse. This configuration improves concurrency without unnecessary compute expense.

NEW QUESTION # 25
An Administrator needs to configure a virtual warehouse in Snowflake for a new use case with these details:
1. There will be 50-100 concurrent users running reports
2. Minimize costs based on the number of active users at a given time
3. The virtual warehouse should suspend and resume automatically based on user activity
Which configuration will meet these requirements?

A. create or replace warehouse reporting_wh
warehouse_size = medium
auto_suspend = 600
auto_resume = true;
B. create or replace warehouse reporting_wh
warehouse_size = medium
max_cluster_count = 10
scaling_policy = standard
auto_suspend = 600
auto_resume = true;
C. create or replace warehouse reporting_wh
warehouse_size = xxxlarge
auto_suspend = 60
auto_resume = true;
D. create or replace warehouse reporting_wh
warehouse_size = xxxlarge
max_cluster_count = 10
scaling_policy = standard
auto_suspend = 600
auto_resume = false;

Answer: B

Explanation:
Supporting 50-100 concurrent users requires a multi-cluster warehouse so compute resources can scale to handle high concurrency. Setting a maximum cluster count allows Snowflake to automatically add clusters when query demand increases and reduce them when demand drops, which helps minimize cost based on active users. Enabling auto_suspend and auto_resume ensures the warehouse automatically stops when idle and restarts when queries arrive, further optimizing cost and operational efficiency.

NEW QUESTION # 26
A Snowflake Administrator needs to persist all virtual warehouse configurations for auditing and backups. Given a table already exists with the following schema:
Table Name: VWH_META
Column 1: SNAPSHOT_TIME TIMESTAMP_NTZ
Column 2: CONFIG VARIANT
Which commands should be executed to persist the warehouse data at the time of execution in JSON format in the table VWH_META?

A. SHOW WAREHOUSES;
INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP(),
FROM TABLE(RESULT_SCAN(LAST_QUERY_ID(1)));
B. SHOW WAREHOUSES;
INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP(),
OBJECT_CONSTRUCT(*)
FROM TABLE(RESULT_SCAN(LAST_QUERY_ID()));
C. SHOW WAREHOUSES;
INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP(), *
FROM TABLE(RESULT_SCAN(LAST_QUERY_ID()));
D. SHOW WAREHOUSES;
INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP(), *
FROM TABLE(RESULT_SCAN(SELECT LAST_QUERY_ID(-1)));

Answer: B

Explanation:
To persist warehouse configurations in JSON format, the result set from SHOW WAREHOUSES must be captured and converted into a variant object. Using OBJECT_CONSTRUCT(*) with RESULT_SCAN(LAST_QUERY_ID()) stores the full warehouse configuration snapshot as JSON in the CONFIG VARIANT column, along with the timestamp.

NEW QUESTION # 27
......

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