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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?
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.
Reference
* Snowflake Documentation on Optimizing Cost1.
* Snowflake Documentation on Controlling Cost2.
What are characteristics of the use of transactions in Snowflake? (Select TWO).
A. Snowflake's transactions can indeed include DDL (Data Definition Language), DML (Data Manipulation Language), and query statements. When executed within a transaction block, they all contribute to the atomicity of the transaction---either all of them commit together or none at all. C. Snowflake supports explicit transaction control through the use of the BEGIN TRANSACTION (or simply BEGIN) and COMMIT statements. Alternatively, the BEGIN WORK and COMMIT WORK syntax is also supported, which is a standard SQL syntax for initiating and ending transactions, respectively. Note: The END TRANSACTION statement is not used in Snowflake to end a transaction; the correct statement is COMMIT or COMMIT WORK.
A DevOps team has a requirement for recovery of staging tables used in a complex set of data pipelines. The staging tables are all located in the same staging schem
a. One of the requirements is to have online recovery of data on a rolling 7-day basis.
After setting up the DATA_RETENTION_TIME_IN_DAYS at the database level, certain tables remain unrecoverable past 1 day.
What would cause this to occur? (Choose two.)
When loading data into a table that captures the load time in a column with a default value of either CURRENT_TIME () or CURRENT_TIMESTAMP () what will occur?
When using the COPY command to load data into Snowflake, if a column has a default value set to CURRENT_TIME() or CURRENT_TIMESTAMP(), all rows loaded by that specific COPY command will have the same timestamp. This is because the default value for the timestamp is evaluated at the start of the COPY operation, and that same value is applied to all rows loaded by that operation.
An Architect needs to design a Snowflake account and database strategy to store and analyze large amounts of structured and semi-structured dat
a. There are many business units and departments within the company. The requirements are scalability, security, and cost efficiency.
What design should be used?
The best design to store and analyze large amounts of structured and semi-structured data for different business units and departments is to use a centralized Snowflake database for core business data, and use separate databases for departmental or project-specific data. This design allows for scalability, security, and cost efficiency by leveraging Snowflake's features such as:
Database cloning:Cloning a database creates a zero-copy clone that shares the same data files as the original database, but can be modified independently. This reduces storage costs and enables fast and consistent data replication for different purposes.
Database sharing:Sharing a database allows granting secure and governed access to a subset of data in a database to other Snowflake accounts or consumers. This enables data collaboration and monetization across different business units or external partners.
A media company needs a data pipeline that will ingest customer review data into a Snowflake table, and apply some transformations. The company also needs to use Amazon Comprehend to do sentiment analysis and make the de-identified final data set available publicly for advertising companies who use different cloud providers in different regions.
The data pipeline needs to run continuously ang efficiently as new records arrive in the object storage leveraging event notifications. Also, the operational complexity, maintenance of the infrastructure, including platform upgrades and security, and the development effort should be minimal.
Which design will meet these requirements?
This design meets all the requirements for the data pipeline. Snowpipe is a feature that enables continuous data loading into Snowflake from object storage using event notifications. It is efficient, scalable, and serverless, meaning it does not require any infrastructure or maintenance from the user. Streams and tasks are features that enable automated data pipelines within Snowflake, using change data capture and scheduled execution. They are also efficient, scalable, and serverless, and they simplify the data transformation process. External functions are functions that can invoke external services or APIs from within Snowflake. They can be used to integrate with Amazon Comprehend and perform sentiment analysis on the data. The results can be written back to a Snowflake table using standard SQL commands. Snowflake Marketplace is a platform that allows data providers to share data with data consumers across different accounts, regions, and cloud platforms. It is a secure and easy way to make data publicly available to other companies.
Snowpipe Overview | Snowflake Documentation
Introduction to Data Pipelines | Snowflake Documentation
External Functions Overview | Snowflake Documentation
Snowflake Data Marketplace Overview | Snowflake Documentation
Which statements describe characteristics of the use of materialized views in Snowflake? (Choose two.)
According to the Snowflake documentation, materialized views have some limitations on the query specification that defines them. One of these limitations is that they cannot include nested subqueries, such as subqueries in the FROM clause or scalar subqueries in the SELECT list. Another limitation is that they cannot include ORDER BY clauses, context functions (such as CURRENT_TIME()), or outer joins. However, materialized views can support MIN and MAX aggregates, as well as other aggregate functions, such as SUM, COUNT, and AVG.
Limitations on Creating Materialized Views | Snowflake Documentation
Exam domains verified against: Official Snowflake ARA-R01 exam guide, last checked October 2026.
Design a Snowflake account and database strategy based on business requirements. Configure identity and access management, multi-tenancy architecture, and data security policies across organizational boundaries.
Evaluate benefits and limitations of various data models in Snowflake. Design data sharing solutions and build architectures that support development lifecycles and complex workload requirements.
Determine appropriate data loading and unloading solutions to meet business needs. Outline key tools in Snowflake's ecosystem and understand how they integrate with Snowflake platforms.
Apply performance tools and best practices to optimize query execution and data storage. Troubleshoot performance issues in existing architectures and select appropriate optimization strategies.
Sample question from this domain above: Q3
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