Snowflake's Cloud Data Warehouse Questions!

Snowflake supports landing data into an external stage on the cloud storage platform. This means that users can load data from external sources directly into Snowflake's cloud-based data warehouse. By utilizing external stages, users can easily ingest and integrate data from various sources, such as files stored in cloud storage platforms like Amazon S3 or Azure Blob Storage, without the need for complex data movement or ETL processes. This feature enhances the flexibility and scalability of Snowflake, allowing users to seamlessly incorporate data from different sources into their analytics workflows.

Data skew occurs when the partitions in a database have disproportionate sizes. This means that some partitions contain significantly more data than others, leading to an imbalance in the distribution of data across the database. This can have negative effects on performance, as queries may take longer to execute on partitions with larger data sizes. Therefore, the statement "True" is correct as it accurately describes data skew in a database.

MFA (Multi-factor Authentication) can be used for connecting to Snowflake via the Snowflake JDBC driver. This means that when accessing Snowflake using the JDBC driver, users can enable MFA to enhance the security of their authentication process. MFA adds an additional layer of verification, requiring users to provide multiple pieces of evidence to prove their identity, such as a password and a unique code from a mobile app. Therefore, the statement "True" is correct.

Snowflake supports data in VARIANTs up to a maximum size of 16 MB compressed. This means that if data is stored in a VARIANT column, it can be up to 16 MB in size when compressed. This limit applies to the overall size of the data, taking into account any compression that may be applied. Therefore, the correct answer is C. 16 MB compressed.

Warehouses can be dynamically expanded to adjust to workloads. This means that warehouses can scale up or down their capacity based on the current workload demands. This flexibility allows for efficient resource allocation and optimization, ensuring that the warehouse can meet the changing needs of the business. By dynamically expanding, warehouses can accommodate increased workloads without compromising performance or efficiency.

When a running warehouse is suspended and then resumed, it is possible for the warehouse cache to be reset. This means that any data or information stored in the cache may be cleared or refreshed. This can happen due to various reasons, such as system maintenance or changes in the warehouse configuration. Therefore, the statement "The warehouse cache may be reset if a running warehouse is suspended and then resumed" is true.

The COPY command is more performant than the INSERT statement because it allows for bulk data loading. When using the COPY command, data can be loaded from a file directly into a table, bypassing the need for individual INSERT statements. This significantly reduces the overhead and improves performance, especially when dealing with large amounts of data. On the other hand, the INSERT statement inserts data row by row, which can be slower and less efficient when dealing with large datasets.

Each worksheet in the UI can have its own role and be set independently. This means that different roles can be assigned to different worksheets, allowing for customization and control over user access and permissions. This flexibility allows for a more tailored and secure user experience within the UI.

The given SQL statement is not efficient in Snowflake because it selects all columns from the table. This means that Snowflake will not be able to perform horizontal pruning effectively, as it cannot eliminate unnecessary columns during query execution. As a result, the query may have to scan through all the columns in the table, leading to slower performance and increased resource usage. To improve efficiency, it is recommended to only select the necessary columns instead of using the asterisk (*) wildcard.

In Snowflake, stages are indeed unique database objects. A stage is a persistent location where data files can be loaded and unloaded. It acts as a temporary storage area for data that is being ingested into or exported out of Snowflake. Stages can be used to efficiently load large amounts of data into Snowflake or export data from Snowflake to an external location. They provide a secure and scalable way to manage data movement in Snowflake. Therefore, the correct answer is true.

The use case and audience play a crucial role in determining the appropriate data modeling techniques to be used. Different use cases may require different levels of complexity and granularity in data modeling. For example, a simple data model may be sufficient for a small-scale application, while a more sophisticated and detailed data model may be necessary for a large enterprise system. Similarly, the audience's level of technical expertise and their specific requirements also influence the selection of data modeling techniques. Therefore, it is true that the use case and audience drive the selection of proven data modeling techniques.

Snowflake optimizes the storage for semi-structured data by identifying and leveraging the repeating elements within the semi-structured strings. This allows Snowflake to efficiently store and process the data, reducing storage costs and improving query performance. By recognizing and capitalizing on the patterns and repetitions in the data, Snowflake can effectively compress and store semi-structured data, making it a true statement that Snowflake optimizes storage for semi-structured data based on repeating elements.

Client-side encryption provides a secure system for managing data in cloud storage because it encrypts the data on the client's device before it is uploaded to the cloud. This means that the data is encrypted and decrypted locally, ensuring that only the client has access to the encryption keys and can decrypt the data. This adds an extra layer of security as it prevents unauthorized access to the data stored in the cloud, even if the cloud storage provider's security measures are compromised.

Snowflake's security and authentication include object-level access. This means that Snowflake's security measures not only cover the overall system and database but also provide granular control over individual objects within the database. Users can be granted or denied access to specific tables, views, or other database objects, ensuring that data is protected at a fine-grained level. This level of security helps in maintaining data integrity and confidentiality within the Snowflake environment.

As new objects are created, the defined privileges are automatically granted to a specified role.

The correct answer is E. All of the above. The ACCOUNTADMIN role in Snowflake can perform all of the mentioned tasks. They can configure parameters at the account level, view and operate on all objects in the account, stop any running SQL statements, and view and manage Snowflake billing and credit data. This role has the highest level of privileges and can perform all administrative tasks within the Snowflake account.

The given correct answer is "True". This means that a user can query a STAGE object. In database management systems, a STAGE object is typically used to temporarily store data before it is loaded into a table. By querying a STAGE object, a user can retrieve and manipulate the data stored in it. This allows for further analysis or processing of the data before it is permanently stored in a table.

Snowflake's processing engine is described as Native SQL because it is designed to process structured query language (SQL) queries directly. Unlike options A, B, and C, which mention specific technologies or frameworks, Native SQL refers to the engine's ability to execute SQL queries without the need for additional tools or frameworks. This makes Snowflake a powerful and efficient platform for working with SQL-based data processing and analytics tasks.

In Snowflake, a table can indeed contain both variant columns and a timestamp. A variant column is a flexible data type that can store semi-structured data, while a timestamp column is used to store date and time values. This allows for greater flexibility and versatility in storing different types of data within a single table.

Different editions of Snowflake instances require separate accounts because each edition has its own set of features, capabilities, and pricing options. By having separate accounts for each edition, organizations can easily manage and control access to specific features and functionalities based on their requirements. This also allows for better scalability and flexibility in terms of resource allocation and usage.

The correct answer is Database Storage. This layer is responsible for storing the data in a compressed, columnar format. Storing data in a compressed format helps to optimize storage space and improve query performance by reducing the amount of data that needs to be read from disk. Columnar storage organizes data by columns rather than rows, which can further enhance query performance by allowing for more efficient data retrieval and processing. Therefore, the Database Storage layer is the most appropriate choice for storing data in a compressed, columnar format.

Virtual warehouses can be resized while queries are running. Resizing a virtual warehouse involves changing the number of compute nodes allocated to it, and this can be done even when queries are running. Resizing allows for scaling up or down the resources allocated to the warehouse, which can improve performance or reduce costs depending on the workload. Therefore, the given statement is false.

Pipes are unique database objects in Snowflake. They are used to load data from external sources into Snowflake tables. Pipes provide a seamless and automated way to ingest data into Snowflake, allowing users to define the data format, location, and other parameters. With pipes, users can easily integrate external data sources with their Snowflake database, making it a powerful feature for data integration and ingestion.

Data Sharing Providers will have to incur the cost of the data storage at normal rates. They may also share a data set with an unlimited number of accounts. Additionally, they have the option to set up and manage "Reader Accounts" for consumers who are not already Snowflake customers. Therefore, the correct answer is D, as it includes all of the mentioned options.

The largest size of a micro-partition is 16 MB when it is compressed. This means that the data within the micro-partition is compressed to reduce its size, allowing for more efficient storage and processing. The compressed size of 16 MB allows for better utilization of storage resources and improved performance in data retrieval and analysis.

A table that consists of a single micro-partition or no micro-partitions will always have a clustering depth of 0 because clustering depth refers to the number of levels in a table's clustering keys. In this case, since there is only one micro-partition or no micro-partitions, there are no levels to consider, resulting in a clustering depth of 0.

In the Snowflake architecture, all security information is stored in the Service layer. This layer is responsible for managing access control, authentication, and encryption of data. It ensures that only authorized users can access the data and provides a secure environment for storing and managing sensitive information. The Storage and Compute layers in Snowflake handle data storage and processing respectively, but the Service layer is specifically designed to handle security-related tasks. Therefore, the correct answer is C. Service.

Snowflake has two key features in their storage architecture: Time Travel and Zero-Copy Cloning. Time Travel allows users to query data as it existed at a specific point in time, providing historical data analysis capabilities. Zero-Copy Cloning enables efficient and fast cloning of data without duplicating it, reducing storage requirements and improving performance. These features are important in Snowflake's architecture as they enhance data accessibility, analysis, and efficiency.

Snowflake includes administration settings for resource consumption in order to help control costs associated with unexpected credit usage of warehouses. This means that Snowflake provides tools and settings that allow users to monitor and manage the amount of credits being used by their warehouses. By having control over resource consumption, users can prevent excessive credit usage and avoid unexpected costs.

The types of tables in Snowflake are Transient, Permanent, and Temporary. Transient tables are used for temporary data storage and are automatically deleted after a specified period of time or when the session ends. Permanent tables store data persistently and are not automatically deleted. Temporary tables are similar to transient tables but are explicitly created and dropped by the user. Therefore, the correct answers are B. Transient, C. Permanent, and E. Temporary.

Snowflake's Cloning allows customers to create a defined data set, which is a point in time snapshot of their data. This snapshot can then be updated by customers, meaning they can make changes or additions to the data set as needed. This feature enables customers to have control over their data and ensure that it is up to date and accurate.

It is important to match the size of the warehouse to the expected size and complexity of the queries to be processed. If the warehouse is too small, it may not be able to handle the volume of data and the complexity of the queries efficiently, leading to slower processing times and potential performance issues. On the other hand, if the warehouse is too large for the expected workload, it may result in unnecessary costs and resources. Therefore, it is crucial to carefully consider the size and complexity of the queries when determining the appropriate size of the warehouse.

False. A customer does not need to have a preexisting account with AWS or Microsoft Azure in order to have a Snowflake account or to use Snowflake. Snowflake is a separate cloud-based data warehousing platform that can be used independently of AWS or Azure. While Snowflake can be integrated with AWS or Azure for additional functionality, it is not a requirement to have an account with either of these platforms to use Snowflake.

Having the majority of objects owned by SYSADMIN is considered a best practice because SYSADMIN is the highest privileged user in a system. By assigning SYSADMIN as the owner of most objects, it ensures that these objects are protected and managed by the most privileged user. This helps in maintaining security, controlling access, and ensuring proper administration of the system.

This statement is true because in most database systems, each user has their own set of permissions and privileges. By default, users cannot access or view the result set of a query executed by another user, unless the necessary permissions have been explicitly granted. This is an important security feature that ensures data privacy and prevents unauthorized access to sensitive information within the database.

a virtual warehouse can be resized at any time.

The statement "The Snowflake Lodge is a community site that does not allow members to post questions" is false. This means that members of the Snowflake Lodge community site are allowed to post questions.

Deleting all rows in a table is a metadata only

Virtual Warehouses is the Compute operation

Reclustering a small table typically doesn't improve query performance significantly because the benefits of reorganizing the data are usually only seen with larger tables. When a table is small, the data is already compact and easily accessible, so there is less opportunity for optimization through reclustering. Additionally, the cost of performing the reclustering operation itself may outweigh any potential performance gains. Therefore, it is generally true that reclustering a small table does not have a significant impact on query performance.

A material view creates a copy of the data based on the view definition

Yes, a query can run against Result Cache with no Virtual Warehouse running and retrieve results (assuming the query is cached). The Result Cache is a separate caching layer that stores the results of frequently executed queries. Even if there is no Virtual Warehouse running, the Result Cache can still hold the cached results and serve them when the same query is executed again.

A consumer account does not have the ability to clone a share, meaning it cannot create an exact replica of the share. However, the share data can still be copied into a table, allowing the consumer account to access and work with the data in a different format. Therefore, the statement "A share can't be cloned by a consumer account, but the share data CAN be copied into a table" is true.

Query processing is the correct answer because this layer in a data management system is responsible for executing user queries and retrieving data from the database. It includes components such as query optimization, query execution, and result handling. Virtual warehouses, which are used for data access in a cloud environment, are typically managed and accessed through the query processing layer. Therefore, this layer contains virtual warehouses for data access.

Snowflake utilizes per second billing, meaning that users are charged based on the actual usage of the platform down to the second. This allows for more accurate and cost-effective billing, as users are only charged for the exact amount of time they use the platform. By offering per second billing, Snowflake ensures that customers are only paying for the resources they actually need, rather than being charged for unused time.

Snowflake supports landing data into internal stages on the cloud storage platform. This means that Snowflake allows users to load data from different sources into internal stages, which are a temporary storage area within Snowflake. These internal stages can then be used to efficiently load data into Snowflake tables. By supporting this feature, Snowflake provides a convenient and flexible way to ingest and process data from various sources within its cloud-based environment.

In a cluster, servers are always removed from the warehouse in reverse order of when they were added, following the LIFO (Last In, First Out) principle. This means that the most recently added server will be the first one to be removed, and the oldest server will be the last one to be removed. Therefore, the given statement that each server in a cluster has a position and is removed in reverse order is true.

Snowflake has three types of caching to optimize performance: Warehouse, Results, and Metadata. The Warehouse cache stores recently accessed data in memory to avoid reading from disk, improving query performance. The Results cache stores the results of recently executed queries, allowing for faster retrieval of the same results. The Metadata cache stores information about the database schema, table structures, and other metadata, reducing the need for frequent metadata queries.

Snowflake provides specific administration features and capabilities to support managing databases and warehouses within a Snowflake account, managing roles and users within a Snowflake account, and monitoring usage and managing resources to control costs in a Snowflake account. However, Snowflake does not provide specific administration features and capabilities to manage 3rd party applications providing data to a Snowflake account.

Tri-secret requires that customers manage their own keys because it is a security measure that ensures the confidentiality and integrity of the customer's data. By managing their own keys, customers have full control over who can access their data and can revoke access at any time. This also protects against unauthorized access and potential data breaches. Additionally, managing their own keys allows customers to comply with regulatory requirements regarding data protection and privacy.

Client-side encryption refers to the process of encrypting data on the client's device before it is sent to the storage layer. This ensures that the data remains encrypted throughout the entire transmission and storage process, providing an added layer of security. By encrypting the data before it is loaded into the storage layer, any potential vulnerabilities or breaches in the storage layer are mitigated, as the data remains encrypted and unreadable without the proper decryption key. This benefit of client-side encryption enhances the overall security and privacy of the stored data.

Clustering keys should be considered by a database designer when the table is very large (multi TB) because clustering keys can help improve the performance of queries on large tables. Additionally, clustering keys should be used when the table is large enough to reside on many micro-partitions, as this can further enhance query performance. Finally, if the columns in the table can provide sufficient filtering to select a subset of these micro-partitions, using clustering keys becomes even more beneficial. Therefore, all of the given options are valid reasons for considering the use of clustering keys.

Snowflake applies software patches to the code base on a weekly basis. This means that they update and fix any issues in their software once every week. This regular schedule allows them to address any bugs or vulnerabilities promptly and ensure that their software is up to date and functioning optimally.

Snowflake Support Services is a service that specifically deals with addressing customer issues. One of the common issues that customers may face is troubleshooting failed queries. Therefore, it can be inferred that Snowflake Support Services does address customer issues related to troubleshooting failed queries. Hence, the answer is true.

The correct answer is D. All of the above. This means that Data Sharing Consumers will have to incur the cost of Compute (virtual warehouse), must create a database based on the share using the ACCOUNTADMIN role, and can query shared objects in the same query that they query their own objects. In other words, they will have to pay for the compute resources, create a database, and have the ability to query shared objects alongside their own objects.

Client-side encryption refers to the process of encrypting data on the client's device before it is sent to the storage service. With client-side encryption, the storage service only receives and stores the encrypted version of the data. This provides an additional layer of security, as the storage service itself does not have access to the unencrypted data. Therefore, the statement that one benefit of client-side encryption is that the storage service layer only contains the encrypted version of the data is true.

Zero-Copy Cloning refers to a technique where only metadata is operated on, without replicating the actual data. It involves storing unmodified data once and storing modified data as new blocks. Therefore, the best description of Zero-Copy Cloning is that it encompasses all of the above options, A, B, and C.

Snowflake provides compute resources for data loading jobs through its managed service. This means that Snowflake takes care of allocating and managing the necessary compute resources required for loading data into the Snowflake platform. Users do not need to worry about provisioning or managing the compute resources themselves, as Snowflake handles it as part of its managed service offering. Therefore, the statement "Compute resources used by Snowflake for data loading jobs can be provided by Snowflake managed service" is true.

Choosing separate accounts in Snowflake enables users to have different editions of Snowflake and different regions, allowing them to customize their Snowflake environment based on their specific needs. Additionally, having separate accounts enables billing at the account level, providing better control and management of costs. It also simplifies the deployment of database objects between environments, making it easier to manage and maintain different versions or configurations. Therefore, all of the given options are correct.

To query a table in Snowflake, the user must be granted all of the mentioned privileges at a minimum. Granting USAGE on the database allows the user to access and use the database. Granting USAGE on the schema allows the user to access and use the schema where the table is located. Granting SELECT on the table allows the user to retrieve data from the table. Therefore, all of these privileges are necessary for the user to successfully query a table in Snowflake.

The correct answer is D. All of the above. This means that all of the options listed (A, B, and C) are security best practices for Snowflake. These practices include ensuring that all objects are owned by the SYSADMIN, all roles and users are owned by the SECURITYADMIN, and granting all of your roles back to SYSADMIN. By following these practices, Snowflake can maintain a secure environment.

When scaling up a Snowflake warehouse, the scaling factor when moving between T-shirt sizes is 2. This means that when upgrading to a larger size, the new warehouse will have double the resources (such as compute power and storage) compared to the previous size.

The correct answer is C. Metadata. Metadata is a type of cache that lives on the Cloud Services layer. Metadata refers to the data that provides information about other data. In the context of cloud services, metadata can include information about the structure, format, and characteristics of data stored in the cloud. This type of cache is used to improve performance and efficiency by storing frequently accessed metadata in a cache to reduce the need for repeated database queries.

The warehouse will never go into suspend mode (i.e. it will always be running and consuming credits)

Snowflake's database architecture is best described as "multi-cluster shared data." This means that Snowflake's architecture allows for multiple clusters to access and share data, enabling parallel processing and scalability. This architecture is designed to handle large amounts of data and provide high performance and concurrency.

No update, no time travel, same region

Resizing the virtual warehouse allows for increased compute resources, which can improve performance by handling larger workloads. Organizing data by granular path can improve performance by reducing the amount of data that needs to be scanned. Splitting input file batches within the recommended range can also improve performance by optimizing the data ingestion process. Therefore, all of these approaches can result in improved performance through linear scaling of data ingestion workload.

Snowflake determines how the data is divided into micro-partitions. Users cannot create or configure these partitions.

In the context of a Cloud Data Warehouse, not all virtual warehouses have access to all data. The access of a virtual warehouse to data can be restricted based on the Database Catalog selected during the creation of the Virtual Warehouse. So, it’s false that all virtual warehouses have access to all data.

These commands can only be executed using SNOWSQL client. They are not supported by ODBC driver.

When selecting a clustering key, the developer should consider several factors. Time dimensions can be important to consider as they can help with organizing and analyzing data based on specific time periods. Join keys are also important to consider as they can help optimize the performance of join operations between tables. Low cardinality columns should be considered as they can help reduce the amount of storage space required for the clustering key. Predicates on tables should also be considered as they can help optimize query performance. Therefore, all of the above factors should be taken into account when selecting a clustering key.

After the one minute - accounts are billed by the second

Snowflake supports all of the mentioned proven data modeling techniques, including 3rd Normal Form, Data Vault, Star Schema, and Snowflake Schema. This means that users can choose the most suitable modeling technique for their specific data requirements and design their data structures accordingly. Snowflake's flexibility in supporting various modeling techniques allows for efficient and optimized data storage and retrieval based on the specific needs of the organization.

The Snowflake architecture consists of multiple layers, including Compute, Storage, and Cloud Services. The Compute layer is responsible for executing queries and processing data, while the Storage layer stores the actual data. Cloud Services layer provides additional functionalities and services for managing and optimizing the Snowflake environment. Therefore, the correct answer includes B. Compute, D. Storage, and G. Cloud Services.

When non-native values such as dates and timestamps are stored as strings in a VARIANT column, operations on these values could be slower. This is because additional parsing and conversion steps may be required to perform calculations or comparisons on the string values. Additionally, storing these values as strings would consume more space compared to storing them in a relational column with the corresponding data type. Therefore, both statements A and B are true.

Snowflake supports various file/data types for data loading including Text Delimited (CSV, TAB, etc.), JSON, XML, Avro, Parquet, and ORC. These file types allow users to load different types of data into Snowflake, enabling flexibility and compatibility with various data sources and formats. PDF is not supported as a file/data type for data loading in Snowflake.

When creating a Virtual Warehouse, two of the available options are Auto-suspend and Auto-resume. Auto-suspend allows the Virtual Warehouse to automatically suspend when it is not being used, helping to save resources and reduce costs. On the other hand, Auto-resume enables the Virtual Warehouse to automatically resume when it is needed again, ensuring that it is always available for use. Therefore, both Auto-suspend and Auto-resume are options that can be selected when creating a Virtual Warehouse.

Cloud services provide centralized services for the data warehouse. Cloud services offer a range of functionalities and resources that can be used to manage and maintain the data warehouse. These services include data storage, data processing, data analytics, and data integration capabilities. By utilizing cloud services, organizations can benefit from scalability, flexibility, and cost-effectiveness in managing their data warehouse infrastructure. Cloud services also provide features such as data security, backup and recovery, and data sharing, which are essential for centralized management of the data warehouse.

Snowflake provides a property called "Scaling_policy" to help control the usage of credits in Auto-scale mode. This property determines the scaling policy to use when automatically starting or shutting down additional clusters.

Only the user who executed a query can access the query results.

Snowpipe is a feature of Snowflake that provides a server-less compute model for loading data into Snowflake. It allows data to be loaded continuously from any internal or external stage without the need for the user to execute a LOADDATA command. Instead, Snowpipe automatically loads the data as soon as it is staged, making option D incorrect.

The number of Snowflake credits consumed is determined by the size of the warehouse because larger warehouses require more resources and therefore consume more credits. Additionally, the duration for which the warehouse runs also affects the consumption of credits as longer running times result in more resource usage. The number of users for the warehouse, however, does not directly impact the consumption of credits.

Referential integrity constraints in Snowflake are informational are not enforced.
Snowflake의 참조 무결성 제약 조건은 정보 제공이며 NOT NULL을 제외하고는 적용되지 않습니다. NOT NULL 이외의 제약 조건은 비활성화 된 것으로 생성됩니다.

A Snowflake Role is indeed the only thing that connects Storage (Database) to Compute (Virtual Warehouse) in Snowflake. Roles in Snowflake are used to manage access privileges and permissions for users and objects within the database. By assigning a role to a user, they gain access to the associated privileges and can perform operations on the database objects. Therefore, a Snowflake Role acts as the bridge between the storage and compute components, allowing users to interact with the data stored in the database through the virtual warehouse.

Snowflake stores the various statistics for databases, tables, columns, and files in the Cloud Services layer. This layer handles all the management and coordination tasks for Snowflake, including metadata management, query optimization, and resource allocation. By storing statistics in the Cloud Services layer, Snowflake can efficiently process queries and optimize performance by leveraging these statistics for query planning and execution.

In a multi-cluster environment, the scaling policies that can be selected are "Standard" and "Economy". The options "Normal" and "Maximize" are not mentioned as available scaling policies. Therefore, the correct answer is B. Standard and C. Economy.

The recommended size of files to be loaded via Snowflake's Snowpipe is 10-100MB compressed. This size range ensures efficient and optimal performance during the loading process. Files within this range can be processed quickly and effectively, minimizing the overall load time and maximizing the system's capabilities.

Worksheet is the name of the query section

The correct answer options C and D, "Maximized" and "Auto-Scale," refer to the modes of a Multi-Cluster Warehouse. "Maximized" mode implies that the warehouse is operating at full capacity, utilizing all available resources to maximize performance. On the other hand, "Auto-Scale" mode allows the warehouse to automatically adjust its resources based on the workload, scaling up or down as needed. These two modes provide flexibility and efficiency in managing and optimizing the Multi-Cluster Warehouse.

When data is staged to a Snowflake internal staging area using the PUT command, the data is encrypted on the client's machine. This means that before the data is transferred to the Snowflake internal staging area, it is encrypted on the client's machine to ensure the security and confidentiality of the data during transit. This encryption ensures that even if the data is intercepted during transfer, it will be unreadable and protected from unauthorized access. Therefore, the statement is true.

Snowflake Support Services addresses customer issues covering individual query syntax improvement. This means that if a customer has a specific query syntax issue or needs help improving their query syntax, they can reach out to Snowflake Support Services for assistance. The support team will provide guidance and help the customer in resolving their query syntax problems.

Snowflake automatically does this for each account. It is built-in and fully managed by Snowflake

If the Credit Quota of a Resource Monitor is reached, suspended warehouses cannot be resumed until one of the following conditions is met: a new billing cycle starts, the credit quota of the monitor is increased, the credit threshold for the trigger is increased, the monitor is no longer assigned to the warehouse, or the monitor is dropped. In other words, any of these conditions need to be fulfilled in order to resume the suspended warehouses.

The Economy Scaling Policy is a setting that aims to conserve credits by prioritizing keeping running clusters fully-loaded instead of starting new clusters. This helps to prevent queries from being queued and taking longer to complete. According to this policy, a cluster will only start if the system estimates that there is enough query load to keep it busy for at least 6 minutes. On the other hand, a cluster will shut down after 5 to 6 consecutive successful checks, performed at 1-minute intervals. These checks determine if the load on the least-loaded cluster can be redistributed to other clusters without the need to spin up the cluster again.

A query profile is used to analyze the execution details of a query. It provides information about the resources used, the execution time, and any errors or warnings encountered during the execution of the query. This information can be used to optimize the query and improve its performance. Statistics provide information about the distribution and characteristics of data, metadata provides information about the structure and properties of the data, and a query plan outlines the steps and operations involved in executing a query. However, none of these options specifically analyze the execution details of a query like a query profile does.

Multi-factor authentication (MFA) is not automatically enabled for all accounts. While it is a crucial security feature, the implementation varies across different platforms. For instance, in Microsoft 365, administrators can enforce MFA for users, but it’s not automatically enabled. Similarly, for Snowflake, MFA is enabled on a per-user basis, and users must enroll themselves. Therefore, it’s false that MFA is automatically enabled for your account and available for all users to self-enroll. It often requires administrative action or individual user setup.

Data sharing in Snowflake is only supported between accounts that are in the same Snowflake region. This means that if two accounts are in different regions, they cannot share data with each other. Data sharing allows organizations to securely share their data with other organizations, enabling collaboration and analysis across different accounts. However, this sharing capability is limited to accounts within the same region to ensure data privacy and compliance with regional regulations.

The standard scaling policy is designed to prevent or minimize queuing by prioritizing the starting of additional clusters instead of conserving credits. When a query is queued or when there is one more query than the currently-running clusters can handle, a new cluster is immediately started. On the other hand, a cluster is shut down after 2 to 3 consecutive successful checks, performed at 1-minute intervals, to determine if the load on the least-loaded cluster can be redistributed to the other clusters without the need to spin up the cluster again.

it can be used for both in-progress and completed queries

MFA (Multi-factor Authentication) login is not only desired for connecting to Snowflake through the web interface but also for accessing Snowflake through other interfaces such as command line tools or API calls. MFA adds an extra layer of security by requiring users to provide multiple pieces of evidence to verify their identity, reducing the risk of unauthorized access to Snowflake. Therefore, the statement that MFA login is desired only for connecting to Snowflake through the web interface is false.

ACCOUNTADMINs are the only users with the privilege to receive resource monitor notifications. This means that they are the only ones who will be alerted when resource usage thresholds are reached or exceeded. Other user roles do not have access to these notifications, making the statement true.

A view is the recommended approach for making a variant column accessible in a BI tool. A view allows users to define a virtual table that is based on the original table, but with modifications such as renaming columns, filtering rows, or combining multiple tables. By creating a view, users can make the variant column accessible by defining the necessary transformations or mappings. This ensures that the data in the variant column can be easily accessed and analyzed using the BI tool.

At the account level, you can have only one resource monitor. This means that you can only monitor the resources of your account using a single resource monitor.

Snowflake security supports user-based access control, meaning that it allows administrators to grant or restrict access to specific users or groups. This feature ensures that only authorized individuals can access and manipulate data within the Snowflake system. By implementing user-based access control, Snowflake enhances data security and helps organizations maintain strict control over their data assets.

Snowflake does not support landing data into bring your own device. Bring your own device (BYOD) refers to the practice of allowing employees to use their personal devices, such as laptops or smartphones, for work purposes. However, Snowflake is a cloud-based data warehousing platform that does not involve the physical storage of data on personal devices. Instead, Snowflake stores data in the cloud and provides secure access to it through various devices, but it does not support the landing of data onto personal devices.

The statement suggests that user managed virtual warehouse can provide compute resources for data loading jobs in Snowflake. This means that users have control over the virtual warehouse and can allocate the necessary compute resources for efficient data loading. Therefore, the correct answer is True.

When dealing with a large complex query, scaling up the cluster is the correct approach. Scaling up the cluster means increasing the resources (such as CPU, memory, storage) of the existing nodes in the cluster. This allows the cluster to handle larger and more complex queries by providing more computing power and storage capacity. Rewriting the query may help optimize its performance, but it is not the primary solution for dealing with a large complex query. Scaling out the cluster, on the other hand, involves adding more nodes to the cluster, which may not be necessary or efficient for handling a single large query.

it cannot exceed - there are no files to copy

Snowflake only deploys within it own VPC.

There is no cost in Snowflake for running backups, purchasing additional hardware, incurring downtime and overhead of additional administration

The role of ACCOUNTADMIN in Snowflake allows a user to administer users and manage all database objects. This role has the highest level of privileges and can perform tasks such as creating and managing databases, tables, and views, as well as granting and revoking permissions for other users. The ACCOUNTADMIN role is typically assigned to administrators or superusers who need full control over the Snowflake account.

A Snowflake table can have only one cluster key. This means that the table can be organized and ordered based on one column, which helps in improving query performance and reducing data storage costs. Having multiple cluster keys would not be possible as it would conflict with the purpose of clustering the data efficiently.

Snowflake does not only work with cloud-based tools. While Snowflake is a cloud-based data platform, it can also integrate with on-premises tools and applications. This allows organizations to leverage Snowflake's capabilities while still utilizing their existing infrastructure. Therefore, the statement that Snowflake only works with cloud-based tools is false.

https://www.snowflake.com/wp-content/uploads/2019/02/Snowflake-Support-Policy-02202019.pdf

B-tree type indexes are not supported by Snowflake's performance optimizing query methods.

Snowflake is a cloud-based data warehouse platform that provides its own compute resources for data loading jobs. Users do not need to provision hardware directly from cloud providers as Snowflake manages the infrastructure and resources required for data loading. Therefore, the correct answer is False.

Cluster keys should not be defined with high cardinality columns. High cardinality columns have many distinct values, which can result in uneven data distribution across the nodes in a cluster. This can lead to performance issues and inefficient query execution. Instead, cluster keys should be defined with low cardinality columns, such as those that have fewer distinct values, to ensure better data distribution and improved performance.

The correct answer is B. COPY & INSERT. Snowflake allows data to be loaded using the COPY command, which efficiently loads large amounts of data from files in various formats. The INSERT command is used to insert individual rows or small amounts of data. Therefore, both commands are used for loading data into Snowflake. The other options, A (COPY & PUT) and C (INSERT & PUT), are not valid commands for loading data into Snowflake.

Snowpipe는 Snowflake에서 제공하는 컴퓨팅 리소스 (예 : 서버리스 컴퓨팅 모델)를 사용합니다.
벌크로드는 COPY 문에 지정된 사용자 제공 가상웨어 하우스에 의존합니다

The Resource Monitor trigger allows for three actions to be taken: suspending the task, suspending the task immediately, and notifying the user. Therefore, options A, C, and D are all valid actions that can be taken from a Resource Monitor trigger.