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Snowflake ARA-C01 Exam Syllabus Topics:

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

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q111-Q116):

NEW QUESTION # 111
A company is designing its serving layer for data that is in cloud storage. Multiple terabytes of the data will be used for reporting. Some data does not have a clear use case but could be useful for experimental analysis.
This experimentation data changes frequently and is sometimes wiped out and replaced completely in a few days.
The company wants to centralize access control, provide a single point of connection for the end-users, and maintain data governance.
What solution meets these requirements while MINIMIZING costs, administrative effort, and development overhead?

A. Import all the data in cloud storage to be used for reporting into a Snowflake schema with native tables.
Then create two different roles with grants to the different datasets to match the different user personas, and grant these roles to the corresponding users.
B. Import all the data in cloud storage to be used for reporting into a Snowflake schema with native tables.
Then create a role that has access to this schema and manage access to the data through that role.
C. Import the data used for reporting into a Snowflake schema with native tables. Then create views that have SELECT commands pointing to the cloud storage files for the experimentation data. Then create two different roles to match the different user personas, and grant these roles to the corresponding users.
D. Import the data used for reporting into a Snowflake schema with native tables. Then create external tables pointing to the cloud storage folders used for the experimentation data. Then create two different roles with grants to the different datasets to match the different user personas, and grant these roles to the corresponding users.

Answer: D

Explanation:
The most cost-effective and administratively efficient solution is to use a combination of native and external tables. Native tables for reporting data ensure performance and governance, while external tables allow for flexibility with frequently changing experimental data. Creating roles with specific grants to datasets aligns with the principle of least privilege, centralizing access control and simplifying user management12.
References
*Snowflake Documentation on Optimizing Cost1.
*Snowflake Documentation on Controlling Cost2.

NEW QUESTION # 112
When activating Tri-Secret Secure in a hierarchical encryption model in a Snowflake account, at what level is the customer-managed key used?

A. At the table level (TMK)
B. At the root level (HSM)
C. At the micro-partition level
D. At the account level (AMK)

Answer: D

Explanation:
Tri-Secret Secure is a feature that allows customers to use their own key, called the customer-managed key (CMK), in addition to the Snowflake-managed key, to create a composite master key that encrypts the data in Snowflake. The composite master key is also known as the account master key (AMK), as it is unique for each account and encrypts the table master keys (TMKs) that encrypt the file keys that encrypt the data files.
The customer-managed key is used at the account level, not at the root level, the table level, or the micro- partition level. The root level is protected by a hardware security module (HSM), the table level is protected by the TMKs, and the micro-partition level is protected by the file keys12. References:
* Understanding Encryption Key Management in Snowflake
* Tri-Secret Secure FAQ for Snowflake on AWS

NEW QUESTION # 113
Which columns can be included in an external table schema? (Select THREE).

A. METADATAS FILE_ROW_NUMBER
B. VALUE
C. METADAT A$ FILENAME
D. METADATASROW_ID
E. METADATASISUPDATE
F. METADATASEXTERNAL TABLE PARTITION

Answer: A,B,C

Explanation:
An external table schema defines the columns and data types of the data stored in an external stage. All external tables include the following columns by default:
* VALUE: A VARIANT type column that represents a single row in the external file.
* METADATA$FILENAME: A pseudocolumn that identifies the name of each staged data file included in the external table, including its path in the stage.
* METADATA$FILE_ROW_NUMBER: A pseudocolumn that shows the row number for each record in a staged data file.
You can also create additional virtual columns as expressions using the VALUE column and/or the pseudocolumns. However, the following columns are not valid for external tables and cannot be included in the schema:
* METADATASROW_ID: This column is only available for internal tables and shows the unique identifier for each row in the table.
* METADATASISUPDATE: This column is only available for internal tables and shows whether the row was inserted or updated by a merge operation.
* METADATASEXTERNAL TABLE PARTITION: This column is not a valid column name and does not exist in Snowflake.
References: Introduction to External Tables, CREATE EXTERNAL TABLE

NEW QUESTION # 114
Which functions does the Data Build Tool (dbt) facilitate? (Select TWO).

A. Data transformation
B. Data loading
C. Data visualization
D. Data replication
E. Data testing

Answer: A,E

Explanation:
dbt is a transformation-focused analytics engineering tool that operates inside the data warehouse. It enables SQL-based data transformations and manages dependencies between models (Answer D). dbt also provides built-in data testing capabilities, allowing teams to define and run tests for data quality, such as uniqueness, not-null constraints, and referential integrity checks (Answer B).
dbt does not handle data loading, visualization, or replication; those functions are typically handled by ingestion tools, BI platforms, or replication services. SnowPro Architect candidates are expected to understand dbt's role in the Snowflake ecosystem and how it fits into modern ELT architectures.

NEW QUESTION # 115
An Architect entered the following commands in sequence:

USER1 cannot find the table.
Which of the following commands does the Architect need to run for USER1 to find the tables using the Principle of Least Privilege? (Choose two.)

A. GRANT ALL PRIVILEGES ON DATABASE SANDBOX TO ROLE INTERN;
B. GRANT USAGE ON DATABASE SANDBOX TO ROLE INTERN;
C. GRANT OWNERSHIP ON DATABASE SANDBOX TO USER INTERN;
D. GRANT USAGE ON SCHEMA SANDBOX.PUBLIC TO ROLE INTERN;
E. GRANT ROLE PUBLIC TO ROLE INTERN;

Answer: B,D

NEW QUESTION # 116
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