ARA-C01 Exam Dumps : SnowPro Advanced: Architect Certification Exam

This question tests Snowflake’s native Git integration setup pattern, which relies on Snowflake security objects to authenticate outbound access to an external Git provider. The correct sequence begins with creating an API integration because it defines and authorizes the external endpoint(s) Snowflake is allowed to communicate with. In Snowflake, integrations are the governance layer for external connectivity—administrators explicitly allow network destinations and control whether the integration is enabled, which is foundational before any credential object can be used.

Next, the Architect creates a secret to securely store the authentication material required by the Git provider (for example, a token or other supported credential). Secrets are designed for securely managing sensitive values and are referenced by other Snowflake objects without exposing the credential in plain text in SQL or configuration.

Finally, the Architect creates the Snowflake Git repository stage, which is the object that actually references the Git repo location and uses the configured integration and secret to authenticate and interact with the repository. Creating the stage last ensures all required prerequisites (allowed connectivity + stored credentials) exist and can be bound to the stage cleanly, aligning with Snowflake’s documented dependency model for external integrations.

In the context of business intelligence (BI) queries, which are typically focused on data analysis and reporting, the star schema is the most suitable data modeling approach.

Option B: Star Schema- The star schema is a type of relational database schema that is widely used for developing data warehouses and data marts for BI purposes. It consists of a central fact table surrounded by dimension tables. The fact table contains the core data metrics, and the dimension tables contain descriptive attributes related to the fact data. The simplicity of the star schema allows for efficient querying and aggregation, which are common operations in BI reporting.

According to the Snowflake documentation, tasks are objects that enable scheduling and execution of SQL statements or JavaScript user-defined functions (UDFs) in Snowflake. Tasks can be used to automate data loading, transformation, and maintenance operations. Snowflake scripting is a feature that allows writing procedural logic using SQL statements and JavaScript UDFs. Snowflake scripting can be used to create complex workflows and orchestrate tasks. Therefore, the best option to automate the daily import of two files from an external stage into Snowflake, join and aggregate the data, and produce a final result set is to create a task using Snowflake scripting that will import the files using the COPY INTO command, and then call a UDF to perform the join and aggregation logic. The UDF can return a table or a variant value as the final result set. References:

Tasks

Snowflake Scripting

User-Defined Functions