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Snowflake ADA-C02 Exam Syllabus Topics:

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

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Snowflake SnowPro Advanced Administrator ADA-C02 Sample Questions (Q28-Q33):

NEW QUESTION # 28
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 # 29
What are characteristics of Dynamic Data Masking? (Choose two.)

A. A masking policy that is currently set on a table can be dropped.
B. A single masking policy can be applied to columns in different tables.
C. The role that creates the masking policy will always see unmasked data in query results.
D. A single masking policy can be applied to columns with different data types.
E. A masking policy can be applied to the VALUE column of an external table.

Answer: A,B

Explanation:
A masking policy applied to a table or column can be dropped or replaced as needed.
The same masking policy can be reused and applied to columns in different tables.

NEW QUESTION # 30
What Snowflake capabilities are commonly used in rollback scenarios? (Choose two.)

A. SELECT SYSTEM$CANCEL_QUERY('problematic_query_id');
B. ALTER TABLE prd_table SWAP WITH prd_table_bkp;
C. Contact Snowflake Support to retrieve Fail-safe data.
D. CREATE TABLE prd_table_bkp CLONE prd_table BEFORE (STATEMENT => 'problematic_query_id');
E. CREATE TABLE prd_table_bkp as SELECT * from table(result_scan('problematic_query_id'));

Answer: B,D

Explanation:
Creating a clone of a table at a point in time before a problematic statement uses Snowflake Time Travel to restore the table’s previous state without copying data. This allows recovery of the table as it existed before the issue occurred.
Swapping tables enables a fast rollback by exchanging the original production table with the restored backup table. This operation is metadata-only and allows immediate restoration of the previous version of the data with minimal downtime.

NEW QUESTION # 31
What is a characteristic of Snowflake's transaction locking and concurrency modeling?

A. Queries executed within a given transaction see that transaction's uncommitted changes.
B. If two queries are concurrently executed against the same table, one of the two queries will be blocked until the other query completes.
C. Transaction locking in Snowflake is enforced exclusively at the row and table levels.
D. A deadlock cannot occur in Snowflake, since concurrently executed queries and DML statements do not block one another.

Answer: D

Explanation:
Snowflake uses multi-version concurrency control (MVCC), which allows queries and DML statements to operate without blocking each other. This architecture eliminates the possibility of deadlocks because transactions work on snapshots of data rather than locking rows or tables in ways that could cause contention.

NEW QUESTION # 32
A company enabled replication between accounts and is ready to replicate data across regions in the same cloud service provider.
The primary database object is : PROD_AWS_EAST. Location : AWS_EAST
The secondary database object is : PROD_AWS_WEST. Location : AWS_WEST
What command and account location is needed to refresh the data?

A. Location : AWS_WEST
Command : ALTER DATABASE PROD_AWS_WEST REFRESH;
B. Location : AWS_WEST
Command : REFRESH DATABASE PROD_AWS_WEST REFRESH;
C. Location : AWS_EAST
Command : ALTER DATABASE PROD_AWS_WEST REFRESH;
D. Location : AWS_EAST
Command : REFRESH DATABASE PROD_AWS_WEST REFRESH;

Answer: A

Explanation:
To update a secondary database with changes from its primary, the ALTER DATABASE <secondary_db> REFRESH; command must be executed in the secondary account/region. In this case, that means running the command on PROD_AWS_WEST in AWS_WEST.

NEW QUESTION # 33
......

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