Free SnowPro Advanced Architect Exam Questions and Answers
SnowPro Advanced Architect is part of the SnowPro certification programme from Snowflake. Every SnowPro credential expires exactly two years after it is awarded, and Snowflake allows only two ways to renew: earn an equal or higher credential, or complete one Snowflake instructor-led training course before it lapses. The tiers are Core at $175, the Specialty series at $225 and the role-based Advanced exams at $375, and the codes carry the revision — COF-C03 is the third version of the core paper. Advanced exams state experience expectations rather than certification prerequisites; the Architect paper asks for two years in production. Snowflake does not publish question counts or durations on its open pages.
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Last updated: October 12, 2026
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Question #1
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?
Correct answer: D
Explanation
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.References: • Snowflake Documentation on Managing Access Control • Snowflake Documentation on Data Sharing
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Question #2
An Architect runs the following SQL query: How can this query be interpreted?
Correct answer: A
Explanation
• A stage is a named location in Snowflake that can store files for data loading and unloading. A stage can be internal or external, depending on where the files are stored. • The query in the question uses the LIST function to list the files in a stage named FILEROWS. The function returns a table with various columns, including FILE_ROW_NUMBER, which is the line number of the file in the stage. • Therefore, the query can be interpreted as listing the files in a stage named FILEROWS and showing the line number of each file in the stage. References: • : Stages • : LIST Function
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Question #3
Is it possible for a data provider account with a Snowflake Business Critical edition to share data with an Enterprise edition data consumer account?
Correct answer: E
Explanation
In Snowflake, data sharing capabilities allow a Business Critical edition account to share data with an Enterprise edition consumer account. The ability to share data is contingent upon the role permissions within the provider account. If a user has the necessary role authority (like ACCOUNTADMIN or a role with similar privileges to create or manage shares), they can add an Enterprise edition account as a consumer. This feature enables flexibility in data sharing across different Snowflake account editions, facilitating broader data collaboration and accessibility.References: Snowflake's data sharing documentation and the specifics of edition-based capabilities discussed in SnowPro Advanced: Architect certification materials.
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Question #4
A company's client application supports multiple authentication methods, and is using Okta. What is the best practice recommendation for the order of priority when applications authenticate to Snowflake?
Correct answer: A
Explanation
This is the best practice recommendation for the order of priority when applications authenticate to Snowflake, according to the Snowflake documentation and the web search results. Authentication is the process of verifying the identity of a user or application that connects to Snowflake. Snowflake supports multiple authentication methods, each with different advantages and disadvantages. The recommended order of priority is based on the following factors: • Security: The authentication method should provide a high level of security and protection against unauthorized access or data breaches. The authentication method should also support multi-factor authentication (MFA) or single sign-on (SSO) for additional security. • Convenience: The authentication method should provide a smooth and easy user experience, without requiring complex or manual steps. The authentication method should also support seamless integration with external identity providers or applications. • Flexibility: The authentication method should provide a range of options and features to suit different use cases and scenarios. The authentication method should also support customization and configuration to meet specific requirements. Based on these factors, the recommended order of priority is: • OAuth (either Snowflake OAuth or External OAuth): OAuth is an open standard for authorization that allows applications to access Snowflake resources on behalf of a user, without exposing the user's credentials. OAuth provides a high level of security, convenience, and flexibility, as it supports MFA, SSO, token- based authentication, and various grant types and scopes. OAuth can be implemented using either Snowflake OAuth or External OAuth, depending on the identity provider and the application12. • External browser: External browser is an authentication method that allows users to log in to Snowflake using a web browser and an external identity provider, such as Okta, Azure AD, or Ping Identity. External browser provides a high level of security and convenience, as it supports MFA, SSO, and federated authentication. External browser also provides a consistent user interface and experience across different platforms and devices34. • Okta native authentication: Okta native authentication is an authentication method that allows users to log in to Snowflake using Okta as the identity provider, without using a web browser. Okta native authentication provides a high level of security and convenience, as it supports MFA, SSO, and federated authentication. Okta native authentication also provides a native user interface and experience for Okta users, and supports various Okta features, such as password policies and user management56. • Key Pair Authentication: Key Pair Authentication is an authentication method that allows users to log in to Snowflake using a public-private key pair, without using a password. Key Pair Authentication provides a high level of security, as it relies on asymmetric encryption and digital signatures. Key Pair Authentication also provides a flexible and customizable authentication option, as it supports various key formats, algorithms, and expiration times. Key Pair Authentication is mostly used for service account users, such as applications or scripts that connect to Snowflake programmatically7 . • Password: Password is the simplest and most basic authentication method that allows users to log in to Snowflake using a username and password. Password provides a low level of security, as it relies on symmetric encryption and is vulnerable to brute force attacks or phishing. Password also provides a low level of convenience and flexibility, as it requires manual input and management, and does not support MFA or SSO. Password is the least recommended authentication method, and should be used only as a last resort or for testing purposes . References: • Snowflake Documentation: Snowflake OAuth • Snowflake Documentation: External OAuth • Snowflake Documentation: External Browser Authentication • Snowflake Blog: How to Use External Browser Authentication with Snowflake • Snowflake Documentation: Okta Native Authentication • Snowflake Blog: How to Use Okta Native Authentication with Snowflake • Snowflake Documentation: Key Pair Authentication • [Snowflake Blog: How to Use Key Pair Authentication with Snowflake] • [Snowflake Documentation: Password Authentication] • [Snowflake Blog: How to Use Password Authentication with Snowflake]
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Question #5
Files arrive in an external stage every 10 seconds from a proprietary system. The files range in size from 500 K to 3 MB. The data must be accessible by dashboards as soon as it arrives. How can a Snowflake Architect meet this requirement with the LEAST amount of coding? (Choose two.)
Select 2 answers.
Correct answer: A, E
Explanation
The requirement is for the data to be accessible as quickly as possible after it arrives in the external stage with minimal coding effort. Option A: Snowpipe with auto-ingest is a service that continuously loads data as it arrives in the stage. With auto-ingest, Snowpipe automatically detects new files as they arrive in a cloud stage and loads the data into the specified Snowflake table with minimal delay and no intervention required. This is an ideal low- maintenance solution for the given scenario where files are arriving at a very high frequency. Option E: Using a combination of a task and a stream allows for real-time change data capture in Snowflake. A stream records changes (inserts, updates, and deletes) made to a table, and a task can be scheduled to trigger on a very short interval, ensuring that changes are processed into the dashboard tables as they occur.
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Question #6
A table for IOT devices that measures water usage is created. The table quickly becomes large and contains more than 2 billion rows. The general query patterns for the table are: * 1. DeviceId, lOT_timestamp and Customerld are frequently used in the filter predicate for the select statement * 2. The columns City and DeviceManuf acturer are often retrieved * 3. There is often a count on Uniqueld Which field(s) should be used for the clustering key?
Correct answer: C
Explanation
A clustering key is a subset of columns or expressions that are used to co- locate the data in the same micro-partitions, which are the units of storage in Snowflake. Clustering can improve the performance of queries that filter on the clustering key columns, as it reduces the amount of data that needs to be scanned. The best choice for a clustering key depends on the query patterns and the data distribution in the table. In this case, the columns DeviceId, IOT_timestamp, and CustomerId are frequently used in the filter predicate for the select statement, which means they are good candidates for the clustering key. The columns City and DeviceManufacturer are often retrieved, but not filtered on, so they are not as important for the clustering key. The column UniqueId is used for counting, but it is not a good choice for the clustering key, as it is likely to have a high cardinality and a uniform distribution, which means it will not help to co-locate the data. Therefore, the best option is to use DeviceId and CustomerId as the clustering key, as they can help to prune the micro-partitions and speed up the queries. References: Clustering Keys & Clustered Tables, Micro-partitions & Data Clustering, A Complete Guide to Snowflake Clustering
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Question #7
A Snowflake Architect is designing a multi-tenant application strategy for an organization in the Snowflake Data Cloud and is considering using an Account Per Tenant strategy. Which requirements will be addressed with this approach? (Choose two.)
Select 2 answers.
Correct answer: B, D
Explanation
The Account Per Tenant strategy involves creating separate Snowflake accounts for each tenant within the multi-tenant application. This approach offers a number of advantages. Option B: With separate accounts, each tenant's environment is isolated, making security and RBAC policies simpler to configure and maintain. This is because each account can have its own set of roles and privileges without the risk of cross-tenant access or the complexity of maintaining a highly granular permission model within a shared environment. Option D: This approach also allows for each tenant to have a unique data shape, meaning that the database schema can be tailored to the specific needs of each tenant without affecting others. This can be essential when tenants have different data models, usage patterns, or application customizations.
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Question #8
What transformations are supported in the below SQL statement? (Select THREE). CREATE PIPE ... AS COPY ... FROM (...)
Select 3 answers.
Correct answer: B, C, D
Explanation
• The SQL statement is a command for creating a pipe in Snowflake, which is an object that defines the COPY INTO <table> statement used by Snowpipe to load data from an ingestion queue into tables1. The statement uses a subquery in the FROM clause to transform the data from the staged files before loading it into the table2. • The transformations supported in the subquery are as follows2: SQLAI-generated code. Review and use carefully. More info on FAQ. create pipe mypipe as copy into mytable from ( select * from @mystage where col1 = 'A' and col2 > 10 ); • uk.co.certification.simulator.questionpool.PList@1a11f5a0 SQLAI-generated code. Review and use carefully. More info on FAQ. create pipe mypipe as copy into mytable (col1, col2, col3) from ( select col3, col1, col2 from @mystage ); • uk.co.certification.simulator.questionpool.PList@1a11f720 SQLAI-generated code. Review and use carefully. More info on FAQ. create pipe mypipe as copy into mytable (col1, col2) from ( select col1, col2 from @mystage ); • The other options are not supported in the subquery because2: SQLAI-generated code. Review and use carefully. More info on FAQ. create pipe mypipe as copy into mytable (col1, col2) from ( select col1::date, col2 from @mystage ); • uk.co.certification.simulator.questionpool.PList@1a11fa70 SQLAI-generated code. Review and use carefully. More info on FAQ. create pipe mypipe as copy into mytable (col1, col2, col3) from ( select s.col1, s.col2, t.col3 from @mystage s join othertable t on s.col1 = t.col1 ); • uk.co.certification.simulator.questionpool.PList@1a11fc60 SQLAI-generated code. Review and use carefully. More info on FAQ. create pipe mypipe as copy into mytable from ( select * from @mystage on error abort ); References: • 1: CREATE PIPE | Snowflake Documentation • 2: Transforming Data During a Load | Snowflake Documentation
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Question #9
When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)
Select 2 answers.
Correct answer: C, D
Explanation
The data formats that are supported for the messages when using the Snowflake Connector for Kafka are Avro and JSON. These are the two formats that the connector can parse and convert into Snowflake table rows. The connector supports both schemaless and schematized JSON, as well as Avro with or without a schema registry1. The other options are incorrect because they are not supported data formats for the messages. CSV, XML, and Parquet are not formats that the connector can parse and convert into Snowflake table rows. If the messages are in these formats, the connector will load them as VARIANT data type and store them as raw strings in the table2. References: Snowflake Connector for Kafka | Snowflake Documentation, Loading Protobuf Data using the Snowflake Connector for Kafka | Snowflake Documentation
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Question #10
What Snowflake features should be leveraged when modeling using Data Vault?
Correct answer: C
Explanation
These two features are relevant for modeling using Data Vault on Snowflake. Data Vault is a data modeling approach that organizes data into hubs, links, and satellites. Data Vault is designed to enable high scalability, flexibility, and performance for data integration and analytics. Snowflake is a cloud data platform that supports various data modeling techniques, including Data Vault. Snowflake provides some features that can enhance the Data Vault modeling, such as: • Snowflake's support of multi-table inserts into the data model's Data Vault tables. Multi-table inserts (MTI) are a feature that allows inserting data from a single query into multiple tables in a single DML statement. MTI can improve the performance and efficiency of loading data into Data Vault tables, especially for real-time or near-real-time data integration. MTI can also reduce the complexity and maintenance of the loading code, as well as the data duplication and latency12. • Scaling up the virtual warehouses will support parallel processing of new source loads. Virtual warehouses are a feature that allows provisioning compute resources on demand for data processing. Virtual warehouses can be scaled up or down by changing the size of the warehouse, which determines the number of servers in the warehouse. Scaling up the virtual warehouses can improve the performance and concurrency of processing new source loads into Data Vault tables, especially for large or complex data sets. Scaling up the virtual warehouses can also leverage the parallelism and distribution of Snowflake's architecture, which can optimize the data loading and querying34. References: • Snowflake Documentation: Multi-table Inserts • Snowflake Blog: Tips for Optimizing the Data Vault Architecture on Snowflake • Snowflake Documentation: Virtual Warehouses • Snowflake Blog: Building a Real-Time Data Vault in Snowflake
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Discussion
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FAQ
Learn More: https://www.snowflake.com/en/resources/learn/certifications/
- Q1: What is the SnowPro Advanced Architect exam?
- A: SnowPro Advanced Architect is a Snowflake certification exam. Judging by the questions in our bank, it concentrates on snowflake, architect, table, tables and query.
- Q2: What topics does the SnowPro Advanced Architect exam cover?
- A: Questions in our SnowPro Advanced Architect bank cluster around snowflake, architect, table, tables, query, snowpipe, column and edition. Working through the full set is the quickest way to find which of these you are weakest on.
- Q3: How should I prepare for SnowPro Advanced Architect?
- A: Work through the SnowPro Advanced Architect practice questions here, checking your answer on each one, then sit the practice test to rehearse the exam under timed conditions before the real thing.
- Q4: Are these real SnowPro Advanced Architect exam questions?
- A: They are drawn from officially released past questions and from community members who have sat SnowPro Advanced Architect. Answers are verified and updated weekly.
- Q5: Where do I register for the SnowPro Advanced Architect exam?
- A: Register through Snowflake directly at https://www.snowflake.com/en/resources/learn/certifications/. Exampractice is not affiliated with Snowflake and does not administer the exam.
- Q6: Is there a free SnowPro Advanced Architect sample?
- A: Yes. Every SnowPro Advanced Architect page shows a free sample of real questions. Upgrading opens the full bank and the practice test.
- Q7: What are Snowflake Certification Exams?
- A: Snowflake Certification Exams validate your expertise in using and managing Snowflake’s cloud-based data platform. These certifications demonstrate your proficiency in deploying, configuring, and optimizing Snowflake solutions to support data warehousing, data lakes, and data sharing within an organization.
- Q8: Why should I pursue Snowflake Certification?
- A: Snowflake Certification enhances your professional credibility, showcasing your skills and knowledge in cloud data solutions. This can lead to better job opportunities, higher salaries, and career advancement in data engineering, data analytics, and IT management roles.
- Q9: What are the benefits of Snowflake Certification?
- A: Benefits include recognition as a certified Snowflake professional, improved job performance, access to exclusive resources, continuing education opportunities, and staying current with the latest Snowflake technologies and best practices.
- Q10: Who should take Snowflake Certification Exams?
- A: Data engineers, data analysts, database administrators, IT professionals, and anyone involved in managing and implementing Snowflake solutions should consider these certifications to validate their expertise and advance their careers.
- Q11: What types of Snowflake Certification Exams are available?
- A: Snowflake offers various certification paths, including:
- Q12: How do I prepare for Snowflake Certification Exams?
- A: Preparation can include official Snowflake training courses, study guides, practice exams, online tutorials, and hands-on experience with Snowflake products and solutions.
- Q13: Where can I take Snowflake Certification Exams?
- A: Snowflake Certification Exams can be taken online with remote proctoring or at authorized testing centers, providing flexibility to fit your schedule and location.
- Q14: How do Snowflake Certifications impact my career?
- A: Snowflake Certifications significantly boost your career by demonstrating your expertise to employers, making you a more competitive candidate for advanced roles and promotions in data engineering, data analytics, and IT management.
- Q15: Are there any prerequisites for Snowflake Certification Exams?
- A: Some exams may have prerequisites, such as foundational knowledge or prior experience with Snowflake products. Check the specific requirements for each certification path on the Snowflake certification website.
- Q16: How often do I need to recertify for Snowflake Certifications?
- A: Snowflake Certifications typically require recertification every two years to ensure that certified professionals stay updated with the latest technologies and industry practices.