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Question 321

Which Snowflake object type is designed to store query results physically for improved performance of eligible recurring queries?

1. Standard view
2. Materialized view
3. External table
4. Secure view

Correct Answer: 2

Explanation

A materialized view stores maintained query results so that eligible queries can potentially retrieve data more efficiently than repeatedly computing the same underlying transformation. Snowflake manages maintenance of the materialized view as the source data changes. A standard view stores a query definition rather than a separate materialized result, while an external table provides metadata-based access to data stored outside Snowflake. A secure view focuses on protecting the view definition and controlling exposure of underlying information. Materialized views are therefore useful for specific recurring query patterns where maintained results can improve performance.

Question 322

Which type of Snowflake view is specifically designed to prevent users from viewing the underlying view definition?

1. Secure view
2. Standard view
3. Materialized view
4. External table

Correct Answer: 1

Explanation

A secure view is designed to prevent unauthorized users from viewing the view’s underlying definition. This makes secure views useful when a provider needs to expose selected data while limiting access to implementation details that could reveal sensitive information. A standard view provides a virtual representation based on its query definition, while a materialized view maintains query results for supported performance scenarios. An external table represents externally stored data through metadata. Secure views are therefore particularly relevant when data access must be provided without exposing the underlying view logic.

Question 323

Which Snowflake object provides a logical representation of data without maintaining a separate stored copy of the query result?

1. Materialized view
2. Standard view
3. External table
4. Dynamic table

Correct Answer: 2

Explanation

A standard view is a logical representation defined by a SQL query rather than a separately maintained copy of its result data. When users query the view, Snowflake evaluates the underlying definition as part of query processing. This makes standard views useful for abstraction, reusable query logic, and controlled presentation of selected columns or rows. Materialized views maintain results for supported performance scenarios, while external tables reference externally stored data. Dynamic tables are designed to maintain query-derived data according to freshness requirements. A standard view therefore provides logical query abstraction without a separately materialized result.

Question 324

Which Snowflake feature allows a table to be created from the result of a SELECT statement?

1. CREATE TABLE AS SELECT
2. CREATE TABLE FROM VIEW
3. COPY TABLE AS SELECT
4. BUILD TABLE QUERY

Correct Answer: 1

Explanation

CREATE TABLE AS SELECT, commonly abbreviated as CTAS, creates a table using the result of a SELECT statement. It is useful when users need to materialize query results into a new table for subsequent processing, reporting, or transformation. The resulting table is independent of the original query after creation unless additional processes are used to keep it synchronized. A standard view would retain the query definition instead of creating a physical table. CTAS is therefore appropriate when the objective is to create a new table from query-derived data.

Question 325

Which Snowflake feature allows a new table to initially share the underlying micro-partitions of an existing table without immediately copying all data?

1. Materialized view
2. Zero-copy cloning
3. External table
4. File format

Correct Answer: 2

Explanation

Zero-copy cloning allows Snowflake users to create a clone of a database, schema, or table without immediately making a complete physical copy of the underlying data. The clone initially references the same underlying micro-partitions, which can make creation fast and storage-efficient. When changes are subsequently made, Snowflake separates modified data as needed. This capability is useful for development, testing, temporary environments, and data recovery workflows. Materialized views, external tables, and file formats serve different purposes and do not provide the same cloning behavior.

Question 326

Which Snowflake table type does not incur Fail-safe storage costs because it is not protected by Fail-safe?

1. Permanent
2. Transient
3. Permanent clustered
4. Secure

Correct Answer: 2

Explanation

Transient tables do not have Fail-safe protection, which distinguishes them from permanent tables. They are intended for data that does not require the additional recovery protection associated with permanent-table Fail-safe storage. Transient tables can still use Time Travel within their configured retention period, but after applicable retention expires, the historical data is not protected by Fail-safe in the same manner as permanent-table data. Permanent tables provide the broader recovery characteristics associated with Snowflake’s lifecycle. Choosing a transient table can therefore be appropriate for temporary or easily reproducible datasets.

Question 327

Which Snowflake table type is automatically removed when the session that created it ends?

1. Permanent table
2. Transient table
3. Temporary table
4. External table

Correct Answer: 3

Explanation

Temporary tables exist only within the session in which they are created and are automatically dropped when that session ends. They are useful for intermediate calculations, temporary transformations, or session-specific workloads where the data should not remain available afterward. Permanent tables persist beyond the creating session, while transient tables persist until explicitly dropped but do not receive Fail-safe protection. External tables reference data stored outside Snowflake. Temporary tables are therefore appropriate when both the table and its data are intended to have a session-limited lifetime.

Question 328

Which table type is generally appropriate for short-lived data that should persist beyond a session but does not require Fail-safe protection?

1. Transient table
2. Temporary table
3. Permanent table
4. Materialized view

Correct Answer: 1

Explanation

A transient table can persist beyond the session that created it while avoiding Fail-safe protection. This makes transient tables useful for intermediate or short-lived datasets that need to remain available for multiple sessions but can be recreated if necessary. Temporary tables are more restrictive because they are session-specific and disappear when the session ends. Permanent tables provide broader data-protection characteristics, while materialized views serve a query-performance purpose rather than representing a general-purpose table type. Transient tables therefore occupy a useful middle ground between temporary and permanent storage.

Question 329

Which Snowflake operation can create a copy of an existing database while initially sharing its underlying data?

1. CREATE DATABASE … CLONE
2. CREATE DATABASE … COPY
3. COPY DATABASE
4. CLONE DATABASE DATA

Correct Answer: 1

Explanation

CREATE DATABASE … CLONE creates a clone of an existing Snowflake database. Like other zero-copy cloning operations, the clone can initially share underlying micro-partitions with its source rather than requiring an immediate full physical copy. This can make development, testing, and environment creation much faster and more storage-efficient. The cloned database can subsequently diverge as changes are made. COPY DATABASE and CLONE DATABASE DATA are not the standard syntax for this operation. The CLONE keyword is the key mechanism used for Snowflake zero-copy cloning.

Question 330

Which Snowflake syntax can create a clone representing an earlier point in time?

1. CREATE TABLE … CLONE … AT
2. CREATE TABLE … HISTORY
3. CREATE TABLE … COPY AT
4. CREATE TABLE … RESTORE

Correct Answer: 1

Explanation

Snowflake supports cloning a table at a historical point using syntax involving CLONE together with AT or BEFORE. This allows users to create a new object based on an earlier state of the source, subject to the availability of historical data. Such historical cloning can be useful for testing, investigation, recovery workflows, or reproducing a prior data state without modifying the original table. The operation is distinct from simply cloning the current table. AT and BEFORE provide the mechanism for identifying the desired historical point.

Question 331

Which Snowflake command can recover a dropped table when the required historical data is still available?

1. RESTORE TABLE
2. UNDROP TABLE
3. RECOVER TABLE
4. RECREATE TABLE

Correct Answer: 2

Explanation

UNDROP TABLE can recover a dropped table when the necessary historical information remains available under Snowflake’s applicable data-retention rules. The operation restores the table object and its recoverable data rather than requiring the user to rebuild the table manually. This is particularly useful after accidental deletion. Once the relevant recovery period has expired, the table may no longer be recoverable through this mechanism. UNDROP is therefore different from CREATE TABLE because it restores an existing dropped object rather than creating a new table from scratch.

Question 332

Which Snowflake object can provide access to files stored in an external cloud location without loading those files into Snowflake-managed table storage?

1. External table
2. Temporary table
3. Materialized view
4. Stream

Correct Answer: 1

Explanation

An external table provides a Snowflake table-like interface to data stored in an external cloud storage location. The data remains outside Snowflake-managed table storage, while Snowflake stores metadata describing the external files and their structure. This approach can be useful when organizations want to query data in cloud storage without first loading it into internal tables. Temporary tables are session-specific, materialized views maintain query results, and streams track changes. External tables therefore provide a bridge between Snowflake SQL and externally stored data.

Question 333

Which file format is commonly associated with columnar analytical data stored in external cloud locations?

1. CSV
2. JSON
3. Parquet
4. XML

Correct Answer: 3

Explanation

Parquet is a columnar file format commonly used for analytical data processing and cloud-based data lakes. Its column-oriented organization can allow engines to read only relevant columns for certain queries, potentially reducing data processing. Snowflake supports Parquet as a semi-structured or structured file format for appropriate ingestion and external-table scenarios. CSV is row-oriented delimited text, while JSON and XML are commonly used for semi-structured document-style data. Parquet is therefore particularly relevant when efficient analytical processing of structured or nested data is required.

Question 334

Which Snowflake capability can automatically maintain transformed data according to a defined freshness target?

1. Dynamic table
2. Standard view
3. File format
4. Resource monitor

Correct Answer: 1

Explanation

Dynamic tables automatically maintain the results of a defined query according to a target freshness requirement called target lag. They are designed for declarative data pipelines in which users specify the desired transformed state rather than manually coordinating every refresh operation. A standard view does not maintain stored results, a file format defines how files are interpreted, and a Resource Monitor manages credit-related thresholds. Dynamic tables can therefore simplify transformation workflows where downstream consumers need data refreshed toward a specified freshness objective.

Question 335

What does the target lag setting of a dynamic table primarily communicate?

1. The desired maximum age of the table’s data
2. The number of warehouse clusters
3. The table’s storage capacity
4. The number of source files

Correct Answer: 1

Explanation

Target lag expresses the desired freshness of a dynamic table’s data relative to changes in its upstream sources. Snowflake uses this requirement when determining how the dynamic table should be refreshed. A shorter target lag generally represents a stronger freshness requirement, while a longer target lag permits less frequent updates. Target lag does not specify the number of warehouse clusters, the physical storage capacity of the table, or the number of source files. It is therefore primarily a data-freshness objective used in dynamic-table pipelines.

Question 336

Which Snowflake feature can automatically refresh a dynamic table according to its configured target lag?

1. Dynamic table refresh mechanism
2. Resource Monitor
3. File format
4. Secure Data Sharing

Correct Answer: 1

Explanation

Dynamic tables use Snowflake’s managed refresh mechanism to maintain their contents toward the configured target lag. Users define the query and freshness requirement, while Snowflake manages the refresh processing needed to maintain the dynamic table. This differs from a traditional manually scheduled workflow where users explicitly coordinate every execution step. Resource Monitors manage credit thresholds, file formats describe staged-file parsing, and Secure Data Sharing controls data access between accounts. The managed refresh behavior is therefore a central characteristic of dynamic tables.

Question 337

Which Snowflake feature is intended to expose selected data while hiding sensitive values in a column according to policy rules?

1. Dynamic masking policy
2. File format
3. Warehouse
4. External stage

Correct Answer: 1

Explanation

A dynamic masking policy controls how sensitive column values are displayed to users based on policy conditions. It can return different representations of the same underlying value depending on the user’s role or other policy logic. This allows organizations to protect sensitive information while still providing access to the underlying table for authorized analytical purposes. File formats concern file parsing, warehouses provide compute resources, and external stages identify external storage locations. Dynamic masking is therefore a security mechanism focused specifically on controlling the presentation of sensitive column data.

Question 338

Which policy type can restrict which rows are visible to a user based on policy-defined conditions?

1. Masking policy
2. Row access policy
3. File format policy
4. Warehouse policy

Correct Answer: 2

Explanation

A row access policy controls which rows are visible from a table or supported object based on policy-defined conditions. This enables organizations to implement row-level filtering for requirements such as business-unit separation, regional access, or user-specific visibility. Unlike a masking policy, which changes how column values are displayed, a row access policy determines whether particular rows are available in the query result. File formats and warehouses do not provide row-level security. Row access policies are therefore appropriate when users should see different subsets of records from the same data object.

Question 339

Which Snowflake capability allows a provider to share selected data with another account without creating a conventional copy of the data?

1. External table
2. Secure Data Sharing
3. Temporary table
4. COPY INTO

Correct Answer: 2

Explanation

Secure Data Sharing allows a Snowflake provider to share selected data with another Snowflake account without creating a traditional physical copy for the consumer. The provider controls which objects are exposed through the share, while the consumer can access the shared data through an appropriate database. This can reduce duplication and simplify collaboration because the provider continues to manage the underlying data. External tables address externally stored data, temporary tables are session-specific, and COPY INTO is used for data movement. Secure Data Sharing is therefore the appropriate collaboration mechanism.

Question 340

Which Snowflake capability is designed to allow consumers to access shared data through a database created from a provider’s share?

1. Consumer database
2. Temporary database
3. Warehouse clone
4. File database

Correct Answer: 1

Explanation

A consumer database provides access to objects made available through a Snowflake share. When a provider shares data with a consumer account, the consumer can create a database from that share and query the permitted shared objects. The consumer database provides a controlled interface to the shared information without requiring the consumer to copy the provider’s underlying data into conventional storage. Temporary databases and file databases are not the standard mechanisms for consuming a share. Consumer databases therefore form an important part of Snowflake’s secure data-sharing architecture.