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Snowflake ADA-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Business Continuity and Disaster Recovery	15%	- Disaster recovery planning 1. Recovery time and point objectives 2. Failover and failback procedures - Data protection and replication 1. Database cloning and backup strategies 2. Time travel and fail-safe configuration 3. Cross-region and cross-cloud replication
Topic 2: Account and Security Administration	30%	- Access control and security 1. Authentication and network policies 2. User and privilege management 3. Role-based access control (RBAC) design 4. Data security and masking policies - Account configuration and management 1. Cost management and billing 2. Organization and account structures 3. Edition and feature configuration
Topic 3: Performance Monitoring and Tuning	20%	- Query performance analysis 1. Materialized views and search optimization 2. Indexing and clustering keys optimization 3. Query profiling and execution plans - System monitoring and troubleshooting 1. Account and warehouse usage metrics 2. Workload isolation and concurrency control 3. Error logging and troubleshooting techniques
Topic 4: Resource Management and Optimization	25%	- Virtual warehouse administration 1. Cost optimization strategies 2. Warehouse sizing, scaling and suspension 3. Workload management and resource monitoring - Database and object management 1. Schema design and object lifecycle 2. Data retention and time travel 3. Storage management and clustering
Topic 5: Data Sharing and Marketplace	10%	- Snowflake Marketplace 1. Listing and consuming data products 2. Marketplace administration and governance - Secure data sharing 1. Secure views and data consumption 2. Shares, readers and data providers

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Snowflake SnowPro Advanced Administrator ADA-C02 Sample Questions (Q19-Q24):

NEW QUESTION # 19
An Administrator has been asked to support the company's application team need to build a loyalty program for its customers. The customer table contains Personal Identifiable Information (PII), and the application team's role is DEVELOPER.
CREATE TABLE customer_data (
customer_first_name string,
customer_last_name string,
customer_address string,
customer_email string,
... some other columns,
);
The application team would like to access the customer data, but the email field must be obfuscated.
How can the Administrator protect the sensitive information, while maintaining the usability of the data?

A. Create a separate table for all the non-PII columns and grant the role DEVELOPER access to the new table.
B. Create a view on the customer_data table to eliminate the email column by omitting it from the SELECT clause. Grant the role DEVELOPER access to the view.
C. Use the CURRENT_ROLE context function to integrate with a masking policy on the fields that contain sensitive data.
D. Use the CURRENT_ROLE and CURRENT_USER context functions to integrate with a secure view and filter the sensitive data.

Answer: C

Explanation:
The correct approach is to apply a dynamic data masking policy on the sensitive customer_email column. Using the CURRENT_ROLE context function in the masking policy allows the Administrator to obfuscate the email for the DEVELOPER role while maintaining usability of the data for other authorized roles.

NEW QUESTION # 20
MY_TABLE is a table that has not been updated or modified for several days. On 01 January 2021 at 07:01, a user executed a query to update this table. The query ID is '8e5d0ca9-005e-44e6-b858-a8f5b37c5726'. It is now 07:30 on the same day.
Which queries will allow the user to view the historical data that was in the table before this query was executed? (Choose three.)

A. SELECT * FROM my_table PRIOR TO STATEMENT '8e5d0ca9-005e-44e6-b858-a8f5b37c5726';
B. SELECT * FROM my_table WITH TIME TRAVEL(OFFSET => -60*30);
C. SELECT * FROM my_table AT(TIMESTAMP => '2021-01-01 07:00:00'::timestamp);
D. SELECT * FROM my_table BEFORE(STATEMENT => '8e5d0ca9-005e-44e6-b858-a8f5b37c5726');
E. SELECT * FROM TIME_TRAVEL('MY_TABLE', 2021-01-01 07:00:00);
F. SELECT * FROM my_table AT(OFFSET => -60*30);

Answer: C,D,F

Explanation:
Use Time Travel to view past table versions: (B) selects the table "as of" 07:00 via AT(TIMESTAMP => ...); (E) selects "as of" 30 minutes earlier via AT(OFFSET => -60*30); (F) selects the state before the specified statement via BEFORE(STATEMENT => '<query_id>').

NEW QUESTION # 21
A team of developers created a new schema for a new project. The developers are assigned the role DEV_TEAM which was set up using the following statements:
USE ROLE SECURITYADMIN;
CREATE ROLE DEV_TEAM;
GRANT USAGE, CREATE SCHEMA ON DATABASE DEV_DB01 TO ROLE DEV_TEAM;
GRANT USAGE ON WAREHOUSE DEV_WH TO ROLE DEV_TEAM;
Each team member's access is set up using the following statements:
USE ROLE SECURITYADMIN;
CREATE ROLE JDOE_PROFILE;
CREATE USER JDOE LOGIN_NAME = 'JDOE' DEFAULT ROLE='JDOE_PROFILE';
GRANT ROLE JDOE_PROFILE TO USER JDOE;
GRANT ROLE DEV_TEAM TO ROLE JDOE_PROFILE;
New tables created by any of the developers are not accessible by the team as a whole.
How can an Administrator address this problem?

A. Set up future grants on the newly-created schemas.
B. Assign ownership privilege to DEV_TEAM on the newly-created schema.
C. Set up the new schema as a managed-access schema.
D. Assign usage privilege on the virtual warehouse DEV_WH to the role JDOE_PROFILE.

Answer: A

Explanation:
Future grants allow privileges to be automatically granted on objects created in the future within a schema. By configuring future grants on the schema, privileges such as SELECT can automatically be granted to the DEV_TEAM role whenever new tables are created. This ensures that all developers using the DEV_TEAM role can access newly created tables without requiring manual privilege grants after each table creation.

NEW QUESTION # 22
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
max_cluster_count = 10
scaling_policy = standard
auto_suspend = 600
auto_resume = true;
B. create or replace warehouse reporting_wh
warehouse_size = xxxlarge
max_cluster_count = 10
scaling_policy = standard
auto_suspend = 600
auto_resume = false;
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 = medium
auto_suspend = 600
auto_resume = true;

Answer: A

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 # 23
What Snowflake capabilities are commonly used in rollback scenarios? (Choose two.)

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

Answer: C,E

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 # 24
......

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