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Snowflake ARA-R01 Exam Questions
- Topic 1: Accounts and Security: This section relates to creating a Snowflake account and a database strategy aligned with business needs. Users are tested for developing an architecture that satisfies data security, privacy, compliance, and governance standards.
- Topic 2: Snowflake Architecture: This section assesses examining the advantages and constraints of different data models, devises data-sharing strategies, and developing architectural solutions that accommodate Development Lifecycles and workload needs.
- Topic 3: Data Engineering: This section is about identifying the optimal data loading or unloading method to fulfill business requirements. Examine the primary tools within Snowflake's ecosystem and their integration with the platform.
- Topic 4: Performance Optimization: This section is about summarizing performance tools, recommended practices, and their ideal application scenarios, addressing performance challenges within current architectures, and resolving them.
Free Snowflake ARA-R01 Exam Actual Questions
Note: Premium Questions for ARA-R01 were last updated On Jul. 15, 2024 (see below)
A company is following the Data Mesh principles, including domain separation, and chose one Snowflake account for its data platform.
An Architect created two data domains to produce two data products. The Architect needs a third data domain that will use both of the data products to create an aggregate data product. The read access to the data products will be granted through a separate role.
Based on the Data Mesh principles, how should the third domain be configured to create the aggregate product if it has been granted the two read roles?
In the scenario described, where a third data domain needs access to two existing data products in a Snowflake account structured according to Data Mesh principles, the best approach is to utilize Snowflake's Data Exchange functionality. Option D is correct as it facilitates the sharing and governance of data across different domains efficiently and securely. Data Exchange allows domains to publish and subscribe to live data products, enabling real-time data collaboration and access management in a governed manner. This approach is in line with Data Mesh principles, which advocate for decentralized data ownership and architecture, enhancing agility and scalability across the organization. Reference:
Snowflake Documentation on Data Exchange
Articles on Data Mesh Principles in Data Management
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?
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.
Reference
* Snowflake Documentation on Search Optimization Service1.
A company is following the Data Mesh principles, including domain separation, and chose one Snowflake account for its data platform.
An Architect created two data domains to produce two data products. The Architect needs a third data domain that will use both of the data products to create an aggregate data product. The read access to the data products will be granted through a separate role.
Based on the Data Mesh principles, how should the third domain be configured to create the aggregate product if it has been granted the two read roles?
In the scenario described, where a third data domain needs access to two existing data products in a Snowflake account structured according to Data Mesh principles, the best approach is to utilize Snowflake's Data Exchange functionality. Option D is correct as it facilitates the sharing and governance of data across different domains efficiently and securely. Data Exchange allows domains to publish and subscribe to live data products, enabling real-time data collaboration and access management in a governed manner. This approach is in line with Data Mesh principles, which advocate for decentralized data ownership and architecture, enhancing agility and scalability across the organization. Reference:
Snowflake Documentation on Data Exchange
Articles on Data Mesh Principles in Data Management
The data share exists between a data provider account and a data consumer account. Five tables from the provider account are being shared with the consumer account. The consumer role has been granted the imported privileges privilege.
What will happen to the consumer account if a new table (table_6) is added to the provider schema?
When a new table (table_6) is added to a schema in the provider's account that is part of a data share, the consumer will not automatically see the new table. The consumer will only be able to access the new table once the appropriate privileges are granted by the provider. The correct process, as outlined in option D, involves using the provider's ACCOUNTADMIN role to grant USAGE privileges on the database and schema, followed by SELECT privileges on the new table, specifically to the share that includes the consumer's database. This ensures that the consumer account can access the new table under the established data sharing setup. Reference:
Snowflake Documentation on Managing Access Control
Snowflake Documentation on Data Sharing
A company is designing a process for importing a large amount of loT JSON data from cloud storage into Snowflake. New sets of loT data get generated and uploaded approximately every 5 minutes.
Once the loT data is in Snowflake, the company needs up-to-date information from an external vendor to join to the dat
a. This data is then presented to users through a dashboard that shows different levels of aggregation. The external vendor is a Snowflake customer.
What solution will MINIMIZE complexity and MAXIMIZE performance?
Using Snowpipe for continuous, automated data ingestion minimizes the need for manual intervention and ensures that data is available in Snowflake promptly after it is generated. Leveraging Snowflake's data sharing capabilities allows for efficient and secure access to the vendor's data without the need for complex API integrations. Materialized views provide pre-aggregated data for fast access, which is ideal for dashboards that require high performance1234.
Reference =
* Snowflake Documentation on Snowpipe4
* Snowflake Documentation on Secure Data Sharing2
* Best Practices for Data Ingestion with Snowflake1
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