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Snowflake ARA-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Accounts and Security	25%	- Governance and Compliance 1. Encryption and security architecture 2. Object ownership and privilege management 3. Data governance strategies - Access Control and Authentication 1. SSO and MFA 2. Role-based access control 3. Data masking and row access policies 4. Network policies
Snowflake Architecture	30%	- Platform Architecture Design 1. Multi-account strategies 2. Organization and account structure 3. Data sharing architecture 4. Cross-region and cross-cloud architecture - Storage and Compute Design 1. Warehouse sizing and scaling 2. Micro-partitions and clustering 3. Database and schema design
Data Engineering	25%	- Data Loading and Pipelines 1. External stages and file formats 2. Bulk and continuous data loading 3. Streams and CDC 4. Snowpipe and tasks - Data Transformation 1. ETL and ELT design 2. Semi-structured data processing 3. Data modeling strategies
Performance Optimization	20%	- Cost and Resource Optimization 1. Resource monitors 2. Concurrency scaling 3. Warehouse cost optimization - Query Performance 1. Query profiling and tuning 2. Caching strategies 3. Materialized views 4. Search optimization service

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q101-Q106):

NEW QUESTION # 101
A healthcare company is deploying a Snowflake account that may include Personal Health Information (PHI). The company must ensure compliance with all relevant privacy standards.
Which best practice recommendations will meet data protection and compliance requirements? (Choose three.)

A. Use the External Tokenization feature to obfuscate sensitive data.
B. Create Dynamic Data Masking policies and apply them to columns that contain PHI.
C. Avoid sharing data with partner organizations.
D. Use, at minimum, the Business Critical edition of Snowflake.
E. Rewrite SQL queries to eliminate projections of PHI data based on current_role().
F. Use the Internal Tokenization feature to obfuscate sensitive data.

Answer: A,B,D

Explanation:
A healthcare company that handles PHI data must ensure compliance with relevant privacy standards, such as HIPAA, HITRUST, and GDPR. Snowflake provides several features and best practices to help customers meet their data protection and compliance requirements1.
One best practice recommendation is to use, at minimum, the Business Critical edition of Snowflake. This edition provides the highest level of data protection and security, including end-to-end encryption with customer-managed keys, enhanced object-level security, and HIPAA and HITRUST compliance2. Therefore, option A is correct.
Another best practice recommendation is to create Dynamic Data Masking policies and apply them to columns that contain PHI. Dynamic Data Masking is a feature that allows masking or redacting sensitive data based on the current user's role. This way, only authorized users can view the unmasked data, while others will see masked values, such as NULL, asterisks, or random characters3. Therefore, option B is correct.
A third best practice recommendation is to use the External Tokenization feature to obfuscate sensitive data. External Tokenization is a feature that allows replacing sensitive data with tokens that are generated and stored by an external service, such as Protegrity. This way, the original data is never stored or processed by Snowflake, and only authorized users can access the tokenized data through the external service4. Therefore, option D is correct.
Option C is incorrect, because the Internal Tokenization feature is not available in Snowflake. Snowflake does not provide any native tokenization functionality, but only supports integration with external tokenization services4.
Option E is incorrect, because rewriting SQL queries to eliminate projections of PHI data based on current_role() is not a best practice. This approach is error-prone, inefficient, and hard to maintain. A better alternative is to use Dynamic Data Masking policies, which can automatically mask data based on the user's role without modifying the queries3.
Option F is incorrect, because avoiding sharing data with partner organizations is not a best practice. Snowflake enables secure and governed data sharing with internal and external consumers, such as business units, customers, or partners. Data sharing does not involve copying or moving data, but only granting access privileges to the shared objects. Data sharing can also leverage Dynamic Data Masking and External Tokenization features to protect sensitive data5.

NEW QUESTION # 102
A Developer is having a performance issue with a Snowflake query. The query receives up to 10 different values for one parameter and then performs an aggregation over the majority of a fact table. It then joins against a smaller dimension table. This parameter value is selected by the different query users when they execute it during business hours. Both the fact and dimension tables are loaded with new data in an overnight import process.
On a Small or Medium-sized virtual warehouse, the query performs slowly. Performance is acceptable on a size Large or bigger warehouse. However, there is no budget to increase costs. The Developer needs a recommendation that does not increase compute costs to run this query.
What should the Architect recommend?

A. Enable the search optimization service on the table. When the users execute the query, the search optimization service will automatically adjust the query execution plan based on the frequently-used parameters.
B. Create a dedicated size Large warehouse for this particular set of queries. Create a new role that has USAGE permission on this warehouse and has the appropriate read permissions over the fact and dimension tables. Have users switch to this role and use this warehouse when they want to access this data.
C. Create a task that will run the 10 different variations of the query corresponding to the 10 different parameters before the users come in to work. The query results will then be cached and ready to respond quickly when the users re-issue the query.
D. Create a task that will run the 10 different variations of the query corresponding to the 10 different parameters before the users come in to work. The task will be scheduled to align with the users' working hours in order to allow the warehouse cache to be used.

Answer: A

Explanation:
Enabling the search optimization service on the table can improve the performance of queries that have selective filtering criteria, which seems to be the case here. This service optimizes the execution of queries by creating a persistent data structure called a search access path, which allows some micro-partitions to be skipped during the scanning process. This can significantly speed up query performance without increasing compute costs1.
References
*Snowflake Documentation on Search Optimization Service1.

NEW QUESTION # 103
A global company needs to securely share its sales and Inventory data with a vendor using a Snowflake account.
The company has its Snowflake account In the AWS eu-west 2 Europe (London) region. The vendor's Snowflake account Is on the Azure platform in the West Europe region. How should the company's Architect configure the data share?

A. 1. Create a share.
2. Add objects to the share.
3. Add a consumer account to the share for the vendor to access.
B. 1. Create a share.
2. Create a reader account for the vendor to use.
3. Add the reader account to the share.
C. 1. Promote an existing database in the company's local account to primary.
2. Replicate the database to Snowflake on Azure in the West-Europe region.
3. Create a share and add objects to the share.
4. Add a consumer account to the share for the vendor to access.
D. 1. Create a new role called db_share.
2. Grant the db_share role privileges to read data from the company database and schema.
3. Create a user for the vendor.
4. Grant the ds_share role to the vendor's users.

Answer: A

Explanation:
The correct way to securely share data with a vendor using a Snowflake account on a different cloud platform and region is to create a share, add objects to the share, and add a consumer account to the share for the vendor to access. This way, the company can control what data is shared, who can access it, and how long the share is valid. The vendor can then query the shared data without copying or moving it to their own account. The other options are either incorrect or inefficient, as they involve creating unnecessary reader accounts, users, roles, or database replication.
https://learn.snowflake.com/en/certifications/snowpro-advanced-architect/

NEW QUESTION # 104
The following chart represents the performance of a virtual warehouse over time:

A Data Engineer notices that the warehouse is queueing queries. The warehouse is sizeX-Small, theminimum and maximum cluster counts are set to 1, thescaling policy is set to standard, andauto-suspend is set to 10 minutes.
How can the performance be improved?

A. Change auto-suspend to a longer time frame.
B. Change the scaling policy to economy.
C. Increase the size of the warehouse.
D. Change the cluster settings.

Answer: D

NEW QUESTION # 105
How can the Snowflake context functions be used to help determine whether a user is authorized to see data that has column-level security enforced? (Select TWO).

A. Set masking policy conditions using current_role targeting the role in use for the current session.
B. Determine if there are ownership privileges on the masking policy that would allow the use of any function.
C. Set masking policy conditions using is_role_in_session targeting the role in use for the current account.
D. Assign the accountadmin role to the user who is executing the object.
E. Set masking policy conditions using invoker_role targeting the executing role in a SQL statement.

Answer: A,E

Explanation:
Snowflake context functions are functions that return information about the current session, user, role, warehouse, database, schema, or object. They can be used to help determine whether a user is authorized to see data that has column-level security enforced by setting masking policy conditions based on the context functions. The following context functions are relevant for column-level security:
* current_role: This function returns the name of the role in use for the current session. It can be used to set masking policy conditions that target the current session and are not affected by the execution context of the SQL statement. For example, a masking policy condition using current_role can allow or deny access to a column based on the role that the user activated in the session.
* invoker_role: This function returns the name of the executing role in a SQL statement. It can be used to set masking policy conditions that target the executing role and are affected by the execution context of the SQL statement. For example, a masking policy condition using invoker_role can allow or deny access to a column based on the role that the user specified in the SQL statement, such as using the AS ROLE clause or a stored procedure.
* is_role_in_session: This function returns TRUE if the user's current role in the session (i.e. the role returned by current_role) inherits the privileges of the specified role. It can be used to set masking policy conditions that involve role hierarchy and privilege inheritance. For example, a masking policy condition using is_role_in_session can allow or deny access to a column based on whether the user's current role is a lower privilege role in the specified role hierarchy.
The other options are not valid ways to use the Snowflake context functions for column-level security:
* Set masking policy conditions using is_role_in_session targeting the role in use for the current account.
This option is incorrect because is_role_in_session does not target the role in use for the current account, but rather the role in use for the current session. Also, the current account is not a role, but rather a logical entity that contains users, roles, warehouses, databases, and other objects.
* Determine if there are ownership privileges on the masking policy that would allow the use of any function. This option is incorrect because ownership privileges on the masking policy do not affect the use of any function, but rather the ability to create, alter, or drop the masking policy. Also, this is not a way to use the Snowflake context functions, but rather a way to check the privileges on the masking policy object.
* Assign the accountadmin role to the user who is executing the object. This option is incorrect because assigning the accountadmin role to the user who is executing the object does not involve using the Snowflake context functions, but rather granting the highest-level role to the user. Also, this is not a recommended practice for column-level security, as it would give the user full access to all objects and data in the account, which could compromise data security and governance.
Context Functions
Advanced Column-level Security topics
Snowflake Data Governance: Column Level Security Overview
Data Security Snowflake Part 2 - Column Level Security

NEW QUESTION # 106
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