Snowflake COF-C03 - SnowPro Core Certification 2026 Exam

The correct answer is B. ALTER STAGE .

Directory tables are associated with stages. To manually refresh the metadata in a directory table, the stage is refreshed using the ALTER STAGE ... REFRESH command.

Why B is correct:

A directory table stores file-level metadata for files in a stage. Since the directory table is tied to the stage, the manual refresh operation is performed through the stage.

Example:

ALTER STAGE my_stage REFRESH;

This refreshes the directory table metadata for the stage.

Why the other options are incorrect:

A. TRUNCATE STAGE is not the command used to refresh directory table metadata.

C. ALTER TABLE is used to modify table properties, not refresh a directory table associated with a stage.

D. ALTER VIEW is used to modify views, not directory tables.

Official Snowflake documentation reference:

Snowflake documentation explains that directory table metadata can be refreshed manually using ALTER STAGE ... REFRESH.

Processing data in smaller batches reduces resource pressure during execution.

Increasing warehouse size provides more memory and CPU, which helps reduce memory spillage , where intermediate data is written to disk.

TheMIN_DATA_RETENTION_TIME_IN_DAYSparameter is set at theAccountlevel in Snowflake. This parameter specifies the minimum number of days Snowflake retains the historical data for time travel, which allows users to access and query data as it existed at previous points in time.

Here ' s how to understand and adjust this parameter:

Purpose of MIN_DATA_RETENTION_TIME_IN_DAYS:This parameter is crucial for managing data lifecycle and compliance requirements within Snowflake. It determines the minimum time frame for which you can perform operations like restoring deleted objects or accessing historical versions of data.

Setting the Parameter:Only account administrators can set or modify this parameter. It is done at the account level, impacting all databases and schemas within the account. The setting can be adjusted based on the organization ' s data retention policy.

Adjusting the Parameter:

To view the current setting, use:

SHOWPARAMETERSLIKE ' MIN_DATA_RETENTION_TIME_IN_DAYS ' ;

To change the setting, an account administrator can execute:

ALTERACCOUNTSETMIN_DATA_RETENTION_TIME_IN_DAYS = < number_of_days > ;

The correct answers are C. Consume datasets and E. Browse exchange listings .

Important correction:

The provided answer A, B is not correct for consumers. Creating and publishing listings are provider actions, not consumer actions.

Why C is correct:

Consumers join a Data Exchange so they can access and consume datasets made available by providers.

Why E is correct:

Consumers can browse listings in the Data Exchange to discover datasets that are available to them.

Why the other options are incorrect:

A. Creating a listing is a provider action.

B. Publishing a listing is a provider or exchange administrator/provider action.

D. Defining listing access is an administrative/provider function, not a typical consumer action.

Official Snowflake documentation reference:

Snowflake documentation describes a Data Exchange as a private hub where providers publish listings and consumers browse and access shared datasets.

Reader accounts are created by data providers for consumers who do not have their own Snowflake accounts. This allows providers to share data without requiring the consumer to create or pay for their own Snowflake account.

While a consumer can access multiple shares via a single reader account , administrative functions (like resource monitors) are managed by the provider.

Snowflake recommends not exposing sequence-generated columns in secure views. Secure views are used to protect sensitive data by ensuring that users can only access data for which they have permissions. Exposing sequence-generated columns can potentially reveal information about the underlying data structure or the number of rows, which might be sensitive.

Create Secure Views:Define secure views using theSECUREkeyword to ensure they comply with Snowflake ' s security policies.

Exclude Sensitive Columns:When creating secure views, exclude columns that might expose sensitive information, such as sequence-generated columns.

CREATE SECURE VIEW secure_view AS

SELECT col1, col2

FROM sensitive_table

WHERE sensitive_column IS NOT NULL;

The GET command is used to download (i.e., unload) files from a Snowflake internal stage to the local file system . COPY INTO writes to stages, not directly to local disk.

Zero-copy cloning initially shares micro-partitions between the source object and the clone. However, when data is modified in either the original or cloned object, Snowflake creates new micro-partitions for the changed data. Those modified micro-partitions consume additional storage.

The correct answer is C. To track how data has been transformed among columns .

Snowflake’s data lineage capability is used to understand how data flows and changes across objects. It helps users see relationships between source and target objects and understand how data is transformed, especially at the column level.

Corrected wording:

The original option said “records,” but Snowflake data lineage is more accurately described as tracking how data is transformed among columns, not individual row-level record transformations.

Why C is correct:

Data lineage helps track how data moves from source columns to target columns through operations such as views, CTAS statements, INSERT statements, and other transformations. This is useful for governance, impact analysis, auditing, and understanding downstream dependencies.

Why the other options are incorrect:

A. Tracking how records are read by a user is more closely related to access history or query history, not data lineage.

B. Tracking dependencies at the object level is related to object dependencies. Data lineage is more specific because it can show how data flows between columns and objects.

D. Snowflake data lineage is not primarily a row-level feature for tracking the impact of transformations on individual records.

Official Snowflake documentation reference:

Snowflake documentation describes data lineage as a governance capability that helps track how data moves and transforms across Snowflake objects, including column-level relationships.

The correct answer is D. By identifying where column-level values are located in each micro-partition .

The Search Optimization Service improves query performance for highly selective queries. It works by creating and maintaining a persistent data structure called a search access path .

The search access path records information about where specific values are located within the table’s micro-partitions. This allows Snowflake to find qualifying rows more efficiently without scanning unnecessary micro-partitions.

Why D is correct:

The search access path helps Snowflake identify which micro-partitions contain column values that match a query predicate. This improves pruning and can speed up selective point lookup queries.

Why the other options are incorrect:

A. Search optimization does not create a real-time index for every database. It is enabled on selected tables and columns.

B. A catalog of tables is not the purpose of the search access path.

C. Query history tracks executed queries. Search optimization does not work by listing previous queries.

Official Snowflake documentation reference:

Snowflake documentation describes the search access path as a persistent data structure maintained by the Search Optimization Service. It helps Snowflake determine which micro-partitions contain values needed by selective queries.

In Snowflake, the use of streams impacts how the data retention period for a table is handled, particularly in scenarios where the stream has not been consumed. The key point to understand is that Snowflake ' s streams are designed to capture data manipulation language (DML) changes such as INSERTS, UPDATES, and DELETES that occur on asource table. Streams maintain a record of these changes until they are consumed by a DML operation or a COPY command that references the stream.

When a stream is created on a table and remains unconsumed, Snowflake extends the data retention period of the table to ensure that the changes captured by the stream are preserved. This extension is specifically up to the point in time represented by the stream ' s offset, which effectively ensures that the data necessary for consuming the stream ' s contents is retained. This mechanism is in place to prevent data loss and ensure the integrity of the stream ' s data, facilitating accurate and reliable data processing and analysis based on the captured DML changes.

This behavior emphasizes the importance of managing streams and their consumption appropriately to balance between data retention needs and storage costs. It ' s also crucial to understand how this temporary extension of the data retention period impacts the overall management of data within Snowflake, including aspects related to data lifecycle, storage cost implications, and the planning of data consumption strategies.

TheRESULT_SCANtable function is used in Snowflake to perform additional processing on the results of a previously-run query. It allows users to reference the result set of a previous query by its query ID, enabling further analysis or transformations without re-executing the original query.

Snowflake Documentation: RESULT_SCAN

The COPY_HISTORY table function in Snowflake is used to track data loading activities, including both manual COPY INTO < table > commands and automated data loading through Snowpipe. This function provides visibility into load operations, making it valuable for monitoring data ingestion, ensuring data integrity, and troubleshooting loading processes.