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Snowflake ARA-C01 Exam Questions
- Topic 1: Design data sharing solutions, based on different use cases/ Determine the appropriate data transformation solution to meet business needs
- Topic 2: Design a Snowflake account and database strategy, based on business requirements/ Troubleshoot performance issues with existing architectures
- Topic 3: Outline the benefits and limitations of various data models in a Snowflake environment/ Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake
- Topic 4: Outline performance tools, best practices, and appropriate scenarios where they should be applied/ Determine the appropriate data recovery solution in Snowflake and how data can be restored
- Topic 5: Determine the appropriate data loading or data unloading solution to meet business needs/ Design an architecture that meets data security, privacy, compliance, and governance requirements
- Topic 6: Create architecture solutions that support Development Lifecycles as well as workload requirements/ Outline Snowflake security principles and identify use cases where they should be applied
Free Snowflake ARA-C01 Exam Actual Questions
Note: Premium Questions for ARA-C01 were last updated On Aug. 22, 2026 (see below)
How can the Snowpipe REST API be used to keep a log of data load history?
Snowpipe is a service that automates and optimizes the loading of data from external stages into Snowflake tables. Snowpipe uses a queue to ingest files as they become available in the stage.Snowpipe also provides REST endpoints to load data and retrieve load history reports1.
The loadHistoryScan endpoint returns the history of files that have been ingested by Snowpipe within a specified time range.The endpoint accepts the following parameters2:
pipe: The fully-qualified name of the pipe to query.
startTimeInclusive: The start of the time range to query, in ISO 8601 format. The value must be within the past 14 days.
endTimeExclusive: The end of the time range to query, in ISO 8601 format. The value must be later than the start time and within the past 14 days.
recentFirst: A boolean flag that indicates whether to return the most recent files first or last. The default value is false, which means the oldest files are returned first.
showSkippedFiles: A boolean flag that indicates whether to include files that were skipped by Snowpipe in the response. The default value is false, which means only files that were loaded are returned.
The loadHistoryScan endpoint can be used to keep a log of data load history by calling it periodically with a suitable time range. The best option among the choices is D, which is to call loadHistoryScan every 10 minutes for a 15-minute time range. This option ensures that the endpoint is called frequently enough to capture the latest files that have been ingested, and that the time range is wide enough to avoid missing any files that may have been delayed or retried by Snowpipe.The other options are either too infrequent, too narrow, or use the wrong endpoint3.
1: Introduction to Snowpipe | Snowflake Documentation
2: loadHistoryScan | Snowflake Documentation
3: Monitoring Snowpipe Load History | Snowflake Documentation
A Snowflake Architect is setting up database replication to support a disaster recovery plan. The primary database has external tables.
How should the database be replicated?
Database replication is a feature that allows you to create a copy of a database in another account, region, or cloud platform for disaster recovery or business continuity purposes. However, not all database objects can be replicated. External tables are one of the exceptions, as they reference data files stored in an external stage that is not part of Snowflake. Therefore, to replicate a database that contains external tables, you need to move the external tables to a separate database that is not replicated, and then replicate the primary database that contains the other objects. This way, you can avoid replication errors and ensure consistency between the primary and secondary databases. The other options are incorrect because they either do not address the issue of external tables, or they use an alternative method that is not supported by Snowflake. You cannot create a clone of the primary database and then replicate it, as replication only works on the original database, not on its clones. You also cannot share the primary database with another account, as sharing is a different feature that does not create a copy of the database, but rather grants access to the shared objects. Finally, you do not need to ensure that the replicated database is in the same region as the external tables, as external tables can access data files stored in any region or cloud platform, as long as the stage URL is valid and accessible.Reference:
[Replication and Failover/Failback]1
[Introduction to External Tables]2
[Working with External Tables]3
[Replication : How to migrate an account from One Cloud Platform or Region to another in Snowflake]4
A company is trying to Ingest 10 TB of CSV data into a Snowflake table using Snowpipe as part of Its migration from a legacy database platform. The records need to be ingested in the MOST performant and cost-effective way.
How can these requirements be met?
For ingesting a large volume of CSV data into Snowflake using Snowpipe, especially for a substantial amount like 10 TB, the on error = SKIP_FILE option in the COPY INTO command can be highly effective. This approach allows Snowpipe to skip over files that cause errors during the ingestion process, thereby not halting or significantly slowing down the overall data load. It helps in maintaining performance and cost-effectiveness by avoiding the reprocessing of problematic files and continuing with the ingestion of other data.
What is the MOST efficient way to design an environment where data retention is not considered critical, and customization needs are to be kept to a minimum?
Transient databases in Snowflake are designed for situations where data retention is not critical, and they do not have the fail-safe period that regular databases have. This means that data in a transient database is not recoverable after the Time Travel retention period. Using a transient database is efficient because it minimizes storage costs while still providing most functionalities of a standard database without the overhead of data protection features that are not needed when data retention is not a concern.
A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.
The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.
What step can be taken to improve the pruning of the reporting tables?
Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.
Reference =
* Snowflake Documentation on micro-partitions and data clustering2
* Community article on recognizing unsatisfactory pruning and improving it1
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