Which of the following are date and time data types in Snowflake? (Choose any 3 options)
TIMEDATE
DATE
Python
TIMESTAMP
DATETIME
JavaScript
Snowflake supports several native data types for managing temporal information:
DATE – Stores dates only (year, month, day) without any time component.
TIMESTAMP – Represents date and time values, including several variants:
• TIMESTAMP_NTZ (no time zone)
• TIMESTAMP_LTZ (local time zone)
• TIMESTAMP_TZ (explicit time zone)
DATETIME – An alias for TIMESTAMP_NTZ, storing both date and time.
These data types enable powerful time-based analytics and comparisons.
❌TIMEDATE is not a valid data type.
❌Python and JavaScript are programming languages, not Snowflake data types.
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What is the primary benefit of the separation of storage and compute in Snowflake?
It allows independent scaling of resources.
It reduces network latency.
It simplifies data governance.
It eliminates the need for data loading.
Snowflake’s architecture separates storage and compute, enabling:
• Compute scaling (up/down or multi-cluster) without changing storage
• Storage expansion without affecting compute
• Cost optimization by paying for compute only when needed
This separation does not impact governance, latency, or data loading requirements.
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What is the purpose of the Public Schema in Snowflake? (Choose any 2 options)
Storing user-specific data
Providing a default schema for new objects
Schema to store Account level meta data
Storing shared resources accessible by all users
The Public schema is created by default within every Snowflake database and serves primarily as a shared workspace that is accessible to all users who have the necessary privileges. One of its main roles is to act as adefault schemafor objects created without explicitly specifying a schema name. This ensures usability and prevents object creation errors when users forget to define a schema. Additionally, the Public schema is commonly used to storeshared or common resourcesthat multiple users or teams need to access. However, it should not be used for sensitive or user-specific data because access can be broad. It does not store account-level metadata; that information resides in INFORMATION_SCHEMA views or account-level metadata functions. Overall, the Public schema acts as both a convenient default location and a shared-access area within a Snowflake database.
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What are virtual warehouses in Snowflake?
A compute resource
A worksheet for writing queries
A type of user account
A storage location for data files
A virtual warehouse in Snowflake is acompute resourcethat supplies CPU, memory, and temporary storage used to process SQL queries, perform data loading, execute DML operations, and run procedural logic. Warehouses are elastic, can be resized on demand, suspended to save costs, and automatically resumed when needed.
Virtual warehouses donotstore data—data is kept in Snowflake’s centralized storage layer. They also are not user accounts; user accounts belong to Snowflake’s identity management system. Worksheets are UI components in Snowsight or Classic Console used to write and run SQL, not compute resources.
Thus, virtual warehouses are Snowflake's compute engine, enabling all processing without managing physical infrastructure.
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Which of the following are key components of Snowflake's RBAC system? (Choose any 3 options)
Permissions
Roles
Privileges
Users
Snowflake’s RBAC security model revolves aroundUsers,Roles, andPrivileges. Users represent individual identities or service accounts. Roles group privileges and are assigned to users. Privileges define specific actions that can be performed on objects (e.g., SELECT, INSERT, OWNERSHIP). “Permissions” is not a formal RBAC component—permissions are effectively the result of privileges assigned to roles. Therefore, the three core RBAC components are Users, Roles, and Privileges.
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What information can be obtained by describing a table in Snowflake? (Choose any 3 options)
Column names and data types
Table constraints
Table Origin
Indexes and keys
The DESCRIBE TABLE (or DESC TABLE) command in Snowflake provides core metadata about table structure. This includescolumn names,data types,nullability, and default values. It also returnsconstraintsif applied, such as PRIMARY KEY, UNIQUE, and CHECK constraints. Snowflake additionally displays information regarding clustering keys and other table characteristics. The command does not show table origin; Snowflake does not track lineage information directly through DESCRIBE TABLE. Indexes in Snowflake are not traditional B-tree indexes—Snowflake uses micro-partition pruning instead—but DESCRIBE TABLE can show clustering keys, which function similarly by enabling optimized data skipping. Therefore, column definitions, constraints, and keys are all valid outputs of DESCRIBE TABLE.
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What is the maximum size limit for a single VARIANT value in Snowflake?
1MB
8MB
32MB
16MB
A single VARIANT value in Snowflake has a maximum size limit of16 MB(uncompressed). This limit applies to semi-structured data stored in VARIANT, such as JSON, XML, Avro, and Parquet objects.
This limit ensures efficient storage, query performance, and micro-partitioning. Exceeding the size results in load or processing errors. For ingestion, when loading large JSON files, it’s recommended to break them into multiple objects or use JSON Lines formatting.
Snowflake has introduced an optional behavior change bundle (2025_03), increasing the limit to128 MBfor accounts that enable it, but the standard default remains 16 MB.
Thus, under default behavior,16MBis the correct maximum value size.
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Which of the following types of data can be found on Snowflake Marketplace? (Choose any 3 options)
Public data sets
Financial market data
Proprietary data sets
Third-party data sets
Snowflake Marketplace serves as a centralized catalog where providers publishready-to-use datasets, models, and applicationsacross industries. It includes:
Public datasets, such as demographics, weather, healthcare statistics, and government data.
Financial market datasets, including equities, commodities, macroeconomic indicators, and pricing feeds from major financial data vendors.
Third-party datasetssupplied by external organizations specializing in geospatial intelligence, retail analytics, marketing insights, healthcare, census data, and more.
“Proprietary datasets” are internal to organizations and typically not published on the public Marketplace unless the owner chooses to list them. Marketplace listings are curated and governed.
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What a Database in Snowflake cant contain?
Views
Tables
Role
Database Role
A Snowflake database is a top-level container that can include schemas, and within those schemas it can contain objects such astables,views,stages,functions,procedures, anddatabase roles. However,global account-level roles(such as SYSADMIN, SECURITYADMIN, PUBLIC, or custom account roles) do not reside inside a database. These roles are created and managed at the Snowflake account level, not within any specific database. In contrast,database rolesare scoped within a specific database and can exist inside it. Views and tables are standard database objects. Therefore, the only option that a Snowflake database cannot contain is an account-levelRole.
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Which of the following are benefits of using a multi-cluster warehouse in Snowflake? (Choose any 2 options)
Reduced storage costs
Improved concurrency for handling many simultaneous queries
Automatic scaling to meet varying query loads
Faster data loading
Amulti-cluster warehouseprovides Snowflake’s highest level of concurrency support by allocating multiple compute clusters behind a single warehouse definition. It automatically adds clusters during peak workload to eliminate query queuing and maintain stable performance for dashboards, BI tools, and multi-user environments.
Improved concurrencyis the primary benefit—large numbers of simultaneous queries are distributed across clusters.
Automatic scaling(scaling out and in) ensures compute cost efficiency, as Snowflake adds clusters only when needed and removes them when load decreases.
Incorrect options:
Storage costs are unaffected because compute and storage are independent.
Faster data loading may occur if warehouse size increases, but multi-cluster design is driven by concurrency, not ingestion performance.
The design enables smooth operation in high-demand enterprise environments.
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Where is unstructured data stored in Snowflake?
In the Cloud Services layer
In internal or external stages
In external tables
In tables with a single VARCHAR column
Unstructured data such as PDF files, images, and other binary documents is stored in stages in Snowflake. These stages may be internal stages, which Snowflake manages directly, or external stages, which reference external cloud storage such as Amazon S3, Azure Blob Storage, or Google Cloud Storage. Stages are the designed mechanism for storing and accessing unstructured files so that they can be processed with functions like PARSE_DOCUMENT or accessed via directory tables.
External tables are used to query structured or semi-structured data (for example, Parquet or JSON) stored in external locations, not to store raw unstructured binary content. The Cloud Services layer coordinates metadata, security, and query services; it does not store user data. Tables with a single VARCHAR column might be used as an improvised approach for small text blobs, but this is not the native or recommended method for managing unstructured data at scale.
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In the Snowsight Query History, what attribute uniquely identifies each query?
Transaction ID
Query ID
Account ID
Session ID
Every query executed in Snowflake is assigned a uniqueQuery ID, a system-generated identifier that allows users to retrieve, analyze, and reference the query. Query IDs support debugging, profile retrieval, audit tracking, workload analysis, and support cases.
Transaction IDs are only assigned to transactional operations and do not uniquely identify all queries.
Session IDs identify user sessions—not individual queries. Many queries can occur in the same session.
Account ID is the identifier for the entire Snowflake account and does not relate to specific queries.
Thus,Query IDis the unique attribute used to identify each query in Query History.
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What does "warehouse scaling in/out" refer to in Snowflake?
Changing the size of the warehouse (e.g., from Small to Medium or vice versa).
Moving data between different storage locations.
Changing the region of the warehouse.
Adjusting the number of clusters in a multi-cluster warehouse.
Scalingin/outin Snowflake refers to modifying thenumber of compute clustersassociated with a multi-cluster virtual warehouse. Scalingoutincreases cluster count to accommodate higher concurrency or workload spikes, allowing more queries to run simultaneously without queuing. Scalinginreduces cluster count during periods of lower demand, optimizing compute usage and costs. This is distinct fromscaling up/down, which refers to changing warehouse size (e.g., Small, Medium). Scaling does not involve data movement or region changes; warehouse compute is stateless and operates independently of storage. Multi-cluster warehouses allow Snowflake to automatically add or remove clusters based on demand when auto-scale policies are configured.
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Which cloud platforms does Snowflake support?
Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Microsoft Azure
All of the options
Snowflake is a fully cloud-native platform that supports deployment across all three major cloud providers:AWS, GCP, and Azure. Snowflake delivers consistent functionality across each provider, allowing organizations to choose the cloud best suited for regulatory, architectural, and business requirements. Although small feature differences may exist between cloud providers, Snowflake’s core capabilities—virtual warehouses, storage layers, security, data sharing, and governance—operate uniformly across all three platforms. This multi-cloud support gives Snowflake strong flexibility for hybrid, multi-region, and multi-cloud deployments.
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What is the LIST command used for in Snowflake?
Lists all the users assigned to a given role.
Lists all the files in a given stage.
Lists all the tables in a specific schema.
Lists all the privileges granted on a specific object.
TheLISTcommand displays all files available in a stage—internal, external, user, or table stages.
It is typically used prior to COPY INTO to confirm which files are available for loading.
SHOW TABLES lists tables; SHOW GRANTS shows privileges; GRANTS queries show user-role assignments—not LIST.
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What is the purpose of the ACCOUNTADMIN role in Snowflake? (Choose any 2 options)
To grant and revoke privileges across the account
To monitor query performance
To create and manage databases
To manage all aspects of the Snowflake account
TheACCOUNTADMINrole is Snowflake’s highest-privileged system-defined role. It provides complete administrative authority across the entire Snowflake account. Its functions include:
Managing global account parameters, replication settings, business continuity, failover groups, and region configurations
Administering billing, resource monitoring, and governance
Granting and revoking privileges across all objects and roles
Overseeing role hierarchy, including SECURITYADMIN and SYSADMIN
It is typically reserved for platform owners and security/governance teams, following least-privilege principles.
“Create and manage databases” is primarily a SYSADMIN responsibility.
“Monitor query performance” can be accomplished by roles with MONITOR privileges; it is not exclusive to ACCOUNTADMIN.
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What is the key difference between a "private listing" and a "public listing" in a Snowflake Data Exchange context?
Public listings require payment, while private listings are free.
Public listings are only accessible to Snowflake employees, while private listings are for external users.
Private listings are shared with specific Snowflake accounts, while public listings are available to all Snowflake users.
Private listings are for sharing code, while public listings are for sharing data.
Aprivate listingis shared only with explicitly selected Snowflake accounts, giving providers fine-grained control over who can access their data. This is ideal for partner organizations, internal business units, or customers requiring restricted access. Apublic listing, on the other hand, is accessible to all Snowflake users via the Marketplace, making it available for broad distribution. Pricing models for both types can be free or paid; neither category inherently requires payment. Both listing types share data, not code. Public listings are not restricted to Snowflake employees—they are open to the entire Snowflake ecosystem. The distinction lies entirely in access scope: targeted (private) vs. universal (public).
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What is the purpose of a role hierarchy in Snowflake?
To define the sequence of SQL queries
To organize roles and grant inherited privileges
To manage network settings
To store raw data
Role hierarchy in Snowflake allows one role to inherit the privileges of another. By granting roles to other roles, Snowflake enables scalable, maintainable access control. Higher-level roles grant privileges downward, allowing administrators to create layered access structures. This hierarchy simplifies permission management across teams and environments. It has no relation to SQL sequencing, network settings, or data storage.
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Which SQL keyword is used to constrain the number of rows returned by a query in Snowflake? (Select TWO)
TOP
SELECT
GET
LIMIT
ROW_NUMBER
Snowflake supports bothTOPandLIMITas valid SQL mechanisms for restricting the number of rows returned by a query. They function similarly but are used in different syntactic positions.
LIMITappears at the end of the query:
SELECT * FROM my_table LIMIT 10;
This tells Snowflake to return only the specified number of rows.
TOPis used in the SELECT clause:
SELECT TOP 10 * FROM my_table;
Both approaches are equivalent in functionality and are supported to maintain compatibility with ANSI SQL and other SQL dialects.
The other options are not correct row-limiting mechanisms:
•SELECTis a required keyword but does not limit rows on its own.
•GETis not a SQL keyword for row restriction; GET is used for downloading files from internal stages.
•ROW_NUMBERis a window function used for ranking rows, not constraining row count.
Therefore, TOP and LIMIT are the only correct SQL keywords in Snowflake for controlling how many rows are returned by a query.
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Changing the size of a virtual warehouse from a Medium to a Large refers to what type of warehouse tuning?
Scaling down
Scaling in
Scaling out
Scaling up
Changing a Snowflake virtual warehouse from Medium to Large increases the compute resources allocated to that warehouse—such as CPU cores, memory, and I/O bandwidth. This process is calledscaling up, or vertical scaling. It is typically performed to improve performance for complex queries, large joins, or computationally heavy workloads.
Scaling down is the reverse—reducing warehouse size from Large to Medium or similar.
Scaling out refers to adding more clusters to a multi-cluster warehouse, enabling increased concurrency rather than increasing power per cluster.
Scaling in is the reverse of scaling out—reducing the number of active clusters.
Thus, increasing the size from Medium to Large is vertical scaling, also known as scaling up.
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Which feature does Snowsight provide for query management?
Manual data storage configuration
Limited to simple queries
Pre-built queries only
An intuitive SQL editor for writing and running queries
Snowsight includes a modern, fully capableSQL editordesigned for rich query development, execution, and analysis. The editor offers features such as syntax highlighting, intelligent auto-complete, contextual error display, and result-set visualization. Users can organize work with worksheets, folders, tagging, and versioning-like behavior.
Snowsight is built for both simple and complex SQL workloads. It supports multi-statement execution, script-like workflows, stored procedure development, materialized views, and advanced analytics queries.
Unsupported options include:
Manual data storage configuration: Snowflake abstracts storage management completely.
Pre-built queries only: Snowsight allows fully custom SQL.
Limited to simple queries: It supports enterprise workloads, BI query chains, and operational SQL.
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What are the benefits of using the Snowsight data loading interface? (Select TWO).
It creates permanent file formats that can be used to load data in the future.
It allows a user to insert the records of a supported file into a table.
It will try to detect data types.
It allows a user to optimize data loading into a table.
It lets a user merge file rows into the table records.
Snowsight’s file-loading interface:
•Automatically detects data typesby inspecting column values.
•Loads (inserts) file contents directly into a table, either a new table or an existing one.
Snowsight does not automatically create permanent file formats, does not merge rows, and does not optimize warehouse-level performance.
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What is the typical syntax for using the LIMIT clause to retrieve the first 10 rows of a table named employees?
SELECT * FROM employees LIMIT 10;
SELECT LIMIT 10 * FROM employees;
LIMIT 10 SELECT * FROM employees;
SELECT * FROM employees WHERE LIMIT 10;
TheLIMITclause is used to restrict the number of rows returned by a query. The correct syntax in Snowflake is:
SELECT * FROM employees LIMIT 10;
This retrieves the first 10 rows of the result set. LIMIT appears at the end of the SELECT statement. Snowflake follows a SQL syntax similar to MySQL/PostgreSQL regarding LIMIT usage.
Incorrect forms include:
Using LIMIT before SELECT
Embedding LIMIT inside WHERE
Reversing the order of SELECT and LIMIT
LIMIT is frequently used for sampling, record previewing, debugging, and exploratory analysis.
Which statement is true about Snowflake Data Exchange? (Choose any 2 options)
It is limited to internal data sharing only
It requires complex ETL processes to transfer data
It supports data sharing between different regions and cloud providers
It allows organizations to securely share live, governed data
Snowflake Data Exchangeprovides governed, real-time data collaboration between Snowflake accounts. It enables providers to publishlive datasetswhile consumers query that data without copying or moving it. Because Snowflake uses secure data sharing primitives at the metadata layer,no ETL pipelinesor data duplication are required.
A key advantage is support forcross-region and cross-cloud sharing, allowing collaboration across AWS, Azure, and GCP regions seamlessly.
Data Exchange listings support controlled visibility, entitlement management, and auditing. Providers maintain full control over updates since consumers always access the live, authoritative version of the dataset.
Incorrect statements:
It is not limited to internal sharing—external sharing is a major feature.
ETL is not required because Snowflake’s architecture exposes shared objects directly.
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What are the three key layers of Snowflake's architecture?
Data Repository, Compute Clusters, Metadata Management
Authentication, Access Control, Cloud Services
Database Storage, ODBC Drivers, Virtual Warehouses
Data Storage, Query Processing, Cloud Services
Snowflake’s architecture is built on three primary layers that separate and optimize storage, compute, and services. TheData Storagelayer stores all structured and semi-structured data in Snowflake’s optimized, compressed columnar format. Snowflake manages file organization, metadata, and optimizations automatically, ensuring efficient storage management. TheQuery Processinglayer is implemented through virtual warehouses that independently execute queries using MPP (massively parallel processing) compute clusters. These warehouses scale elastically based on workload requirements. TheCloud Serviceslayer manages metadata, authentication, access control, query optimization, and infrastructure orchestration. This separation allows independent scaling of compute and storage, optimizing performance while simplifying administration.
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What is a key characteristic of the Snowflake architecture's Cloud Services Layer?
It stores all customer data.
It manages virtual warehouses.
It handles security and metadata management.
It provides the user interface for Snowsight.
The Cloud Services Layer is the coordination and control layer of Snowflake’s architecture. One of its primary responsibilities is managing security, metadata, authentication, and system-wide services. This layer handles user authentication, role-based access control, metadata services (such as table structures, micro-partition metadata, statistics), query parsing, optimization, execution coordination, and transaction management.
It does not store customer data; storage is handled by the Database Storage Layer using micro-partitions. It does not manage virtual warehouses directly; warehouses are part of the Compute Layer. While Snowsight is a UI that interacts with the Cloud Services Layer, the interface itself is not part of the architectural layer.
The Cloud Services Layer essentially acts as the “brain” of Snowflake, ensuring the platform is consistent, secure, optimized, and able to scale operations intelligently across compute clusters and cloud-native storage environments.
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Which of the following parameters can be used with the COPY INTO