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NEW QUESTION # 45
An Architect would like to save quarter-end financial results for the previous six years.
Which Snowflake feature can the Architect use to accomplish this?
- A. Search optimization service
- B. Secure views
- C. Zero-copy cloning
- D. Time Travel
- E. Materialized view
Answer: C
NEW QUESTION # 46
In the default access control hierarchy, both securityadmin and sysadmin are owned by accountadmin
- A. TRUE
- B. FALSE
Answer: A
NEW QUESTION # 47
A company has several sites in different regions from which the company wants to ingest data.
Which of the following will enable this type of data ingestion?
- A. The company should use a storage integration for the external stage.
- B. The company must replicate data between Snowflake accounts.
- C. The company must have a Snowflake account in each cloud region to be able to ingest data to that account.
- D. The company should provision a reader account to each site and ingest the data through the reader accounts.
Answer: A
Explanation:
This is the correct answer because it allows the company to ingest data from different regions using a storage integration for the external stage. A storage integration is a feature that enables secure and easy access to files in external cloud storage from Snowflake. A storage integration can be used to create an external stage, which is a named location that references the files in the external storage. An external stage can be used to load data into Snowflake tables using the COPY INTO command, or to unload data from Snowflake tables using the COPY INTO LOCATION command. A storage integration can support multiple regions and cloud platforms, as long as the external storage service is compatible with Snowflake12.
References:
* Snowflake Documentation: Storage Integrations
* Snowflake Documentation: External Stages
NEW QUESTION # 48
A company's Architect needs to find an efficient way to get data from an external partner, who is also a Snowflake user. The current solution is based on daily JSON extracts that are placed on an FTP server and uploaded to Snowflake manually. The files are changed several times each month, and the ingestion process needs to be adapted to accommodate these changes.
What would be the MOST efficient solution?
- A. Ask the partner to set up a Snowflake reader account and use that account to get the data for ingestion.
- B. Ask the partner to use the data lake export feature and place the data into cloud storage where Snowflake can natively ingest it (schema-on-read).
- C. Ask the partner to create a share and add the company's account.
- D. Keep the current structure but request that the partner stop changing files, instead only appending new files.
Answer: C
Explanation:
The most efficient solution is to ask the partner to create a share and add the company's account (Option A).
This way, the company can access the live data from the partner without any data movement or manual intervention. Snowflake's secure data sharing feature allows data providers to share selected objects in a database with other Snowflake accounts. The shared data is read-only and does not incur any storage or compute costs for the data consumers. The data consumers can query the shared data directly or create local copies of the shared objects in their own databases. Option B is not efficient because it involves using the data lake export feature, which is intended for exporting data from Snowflake to an external data lake, not for importing data from another Snowflake account. The data lake export feature also requires the data provider to create an external stage on cloud storage and use the COPY INTO <location> command to export the data into parquet files. The data consumer then needs to create an external table or a file format to load the data from the cloud storage into Snowflake. This process can be complex and costly, especially if the data changes frequently. Option C is not efficient because it does not solve the problem of manual data ingestion and adaptation. Keeping the current structure of daily JSON extracts on an FTP server and requesting the partner to stop changing files, instead only appending new files, does not improve the efficiency or reliability of the data ingestion process. The company still needs to upload the data to Snowflake manually and deal with any schema changes or data quality issues. Option D is not efficient because it requires the partner to set up a Snowflake reader account and use that account to get the data for ingestion. A reader account is a special type of account that can only consume data from the provider account that created it. It is intended for data consumers who are not Snowflake customers and do not have a licensing agreement with Snowflake. A reader account is not suitable for data ingestion from another Snowflake account, as it does not allow uploading, modifying, or unloading data. The company would need to use external tools or interfaces to access the data from the reader account and load it into their own account, which can be slow and expensive. References: The answer can be verified from Snowflake's official documentation on secure data sharing, data lake export, and reader accounts available on their website. Here are some relevant links:
* Introduction to Secure Data Sharing | Snowflake Documentation
* Data Lake Export Public Preview Is Now Available on Snowflake | Snowflake Blog
* Managing Reader Accounts | Snowflake Documentation
NEW QUESTION # 49
One of your colleagues has submitted a long running query in Snowflake. how long the query can run till snowflake automatically cancels the query?
- A. 24 hours
- B. 14 hours
- C. 2 hours
- D. 2 days
Answer: D
NEW QUESTION # 50
The IT Security team has identified that there is an ongoing credential stuffing attack on many of their organization's system.
What is the BEST way to find recent and ongoing login attempts to Snowflake?
- A. Query the LOGIN_HISTORY view in the ACCOUNT_USAGE schema in the SNOWFLAKE database.
- B. View the Users section in the Account tab in the Snowflake UI and review the last login column.
- C. View the History tab in the Snowflake UI and set up a filter for SQL text that contains the text "LOGIN".
- D. Call the LOGIN_HISTORY Information Schema table function.
Answer: D
NEW QUESTION # 51
Which Snowflake data modeling approach is designed for BI queries?
- A. Star schema
- B. Data Vault
- C. Snowflake schema
- D. 3 NF
Answer: A
Explanation:
A star schema is a Snowflake data modeling approach that is designed for BI queries. A star schema is a type of dimensional modeling that organizes data into fact tables and dimension tables. A fact table contains the measures or metrics of the business process, such as sales amount, order quantity, or profit margin. A dimension table contains the attributes or descriptors of the business process, such as product name, customer name, or order date. A star schema is called so because it resembles a star, with one fact table in the center and multiple dimension tables radiating from it. A star schema can improve the performance and simplicity of BI queries by reducing the number of joins, providing fast access to aggregated data, and enabling intuitive query syntax. A star schema can also support various types of analysis, such as trend analysis, slice and dice, drill down, and roll up12.
References:
* Snowflake Documentation: Dimensional Modeling
* Snowflake Documentation: Star Schema
NEW QUESTION # 52
Which of the below commands will use warehouse credits?
- A. SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID;
- B. SHOW TABLES LIKE 'SNOWFL%';
- C. SELECT MAX(FLAKE_ID) FROM SNOWFLAKE;
- D. SELECT COUNT(*) FROM SNOWFLAKE;
Answer: A,C,D
Explanation:
Warehouse credits are used to pay for the processing time used by each virtual warehouse in Snowflake. A virtual warehouse is a cluster of compute resources that enables executing queries, loading data, and performing other DML operations. Warehouse credits are charged based on the number of virtual warehouses you use, how long they run, and their size1.
Among the commands listed in the question, the following ones will use warehouse credits:
SELECT MAX(FLAKE_ID) FROM SNOWFLAKE: This command will use warehouse credits because it is a query that requires a virtual warehouse to execute. The query will scan the SNOWFLAKE table and return the maximum value of the FLAKE_ID column2. Therefore, option B is correct.
SELECT COUNT(*) FROM SNOWFLAKE: This command will also use warehouse credits because it is a query that requires a virtual warehouse to execute. The query will scan the SNOWFLAKE table and return the number of rows in the table3. Therefore, option C is correct.
SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID: This command will also use warehouse credits because it is a query that requires a virtual warehouse to execute. The query will scan the SNOWFLAKE table and return the number of rows for each distinct value of the FLAKE_ID column4. Therefore, option D is correct.
The command that will not use warehouse credits is:
SHOW TABLES LIKE 'SNOWFL%': This command will not use warehouse credits because it is a metadata operation that does not require a virtual warehouse to execute. The command will return the names of the tables that match the pattern 'SNOWFL%' in the current database and schema5. Therefore, option A is incorrect.
NEW QUESTION # 53
A user is executing the following command sequentially within a timeframe of 10 minutes from start to finish:
What would be the output of this query?
- A. The offset -> is not a valid clause in the clone operation.
- B. Syntax error line 1 at position 58 unexpected 'at'.
- C. Time Travel data is not available for table T_SALES.
- D. Table T_SALES_CLONE successfully created.
Answer: D
Explanation:
The query is executing a clone operation on an existing table t_sales with an offset to account for the retention time. The syntax used is correct for cloning a table in Snowflake, and the use of the at(offset => -60*30) clause is valid. This specifies that the clone should be based on the state of the table 30 minutes prior (60 seconds * 30). Assuming the table t_sales exists and has been modified within the last 30 minutes, and considering the data_retention_time_in_days is set to 1 day (which enables time travel queries for the past 24 hours), the table t_sales_clone would be successfully created based on the state of t_sales 30 minutes before the clone command was issued.
NEW QUESTION # 54
You have a view.
How will you list all the object references of the view?
- A. GET_VIEW_METADATA
- B. GET_VIEW_REFERENCES
- C. GET_OBJECT_REFERENCES
Answer: C
NEW QUESTION # 55
An Architect needs to allow a user to create a database from an inbound share.
To meet this requirement, the user's role must have which privileges? (Choose two.)
- A. IMPORT PRIVILEGES;
- B. IMPORT SHARE;
- C. CREATE SHARE;
- D. IMPORT DATABASE;
- E. CREATE DATABASE;
Answer: D,E
Explanation:
According to the Snowflake documentation, to create a database from an inbound share, the user's role must have the following privileges:
The CREATE DATABASE privilege on the current account. This privilege allows the user to create a new database in the account1.
The IMPORT DATABASE privilege on the share. This privilege allows the user to import a database from the share into the account2. The other privileges listed are not relevant for this requirement. The IMPORT SHARE privilege is used to import a share into the account, not a database3. The IMPORT PRIVILEGES privilege is used to import the privileges granted on the shared objects, not the objects themselves2. The CREATE SHARE privilege is used to create a share to provide data to other accounts, not to consume data from other accounts4.
Reference:
CREATE DATABASE | Snowflake Documentation
Importing Data from a Share | Snowflake Documentation
Importing a Share | Snowflake Documentation
CREATE SHARE | Snowflake Documentation
NEW QUESTION # 56
Which of the below operations are allowed on an inbound share data?
- A. CREATE/DROP/ALTER TABLE
- B. MERGE
- C. INSERT INTO
- D. SELECT WITH GROUP BY
- E. ALTER SCHEMA
- F. SELECT WITH JOIN
Answer: D,F
NEW QUESTION # 57
The diagram shows the process flow for Snowpipe auto-ingest with Amazon Simple Notification Service (SNS) with the following steps:
Step 1: Data files are loaded in a stage.
Step 2: An Amazon S3 event notification, published by SNS, informs Snowpipe - by way of Amazon Simple Queue Service (SQS) - that files are ready to load. Snowpipe copies the files into a queue.
Step 3: A Snowflake-provided virtual warehouse loads data from the queued files into the target table based on parameters defined in the specified pipe.
If an AWS Administrator accidentally deletes the SQS subscription to the SNS topic in Step 2, what will happen to the pipe that references the topic to receive event messages from Amazon S3?
- A. The pipe will continue to receive the messages as Snowflake will automatically restore the subscription by creating a new SNS topic. Snowflake will then recreate the pipe by specifying the new SNS topic name in the pipe definition.
- B. The pipe will no longer be able to receive the messages and the user must wait for 24 hours from the time when the SNS topic subscription was deleted. Pipe recreation is not required as the pipe will reuse the same subscription to the existing SNS topic after 24 hours.
- C. The pipe will no longer be able to receive the messages. To restore the system immediately, the user needs to manually create a new SNS topic with a different name and then recreate the pipe by specifying the new SNS topic name in the pipe definition.
- D. The pipe will continue to receive the messages as Snowflake will automatically restore the subscription to the same SNS topic and will recreate the pipe by specifying the same SNS topic name in the pipe definition.
Answer: C
Explanation:
If an AWS Administrator accidentally deletes the SQS subscription to the SNS topic in Step 2, the pipe that references the topic to receive event messages from Amazon S3 will no longer be able to receive the messages.
This is because the SQS subscription is the link between the SNS topic and the Snowpipe notification channel.
Without the subscription, the SNS topic will not be able to send notifications to the Snowpipe queue, and the pipe will not be triggered to load the new files. To restore the system immediately, the user needs to manually create a new SNS topic with a different name and then recreate the pipe by specifying the new SNS topic name in the pipe definition. This will create a new notification channel and a new SQS subscription for the pipe. Alternatively, the user can also recreate the SQS subscription to the existing SNS topic and then alter the pipe to use the same SNS topic name in the pipe definition. This will also restore the notification channel and the pipe functionality. References:
* Automating Snowpipe for Amazon S3
* Enabling Snowpipe Error Notifications for Amazon SNS
* HowTo: Configuration steps for Snowpipe Auto-Ingest with AWS S3 Stages
NEW QUESTION # 58
Which data models can be used when modeling tables in a Snowflake environment? (Select THREE).
- A. Graph model
- B. Data vault
- C. Dimensional/Kimball
- D. Bayesian hierarchical model
- E. Data lake
- F. lnmon/3NF
Answer: B,C,F
Explanation:
Snowflake is a cloud data platform that supports various data models for modeling tables in a Snowflake environment. The data models can be classified into two categories: dimensional and normalized. Dimensional data models are designed to optimize query performance and ease of use for business intelligence and analytics. Normalized data models are designed to reduce data redundancy and ensure data integrity for transactional and operational systems. The following are some of the data models that can be used in Snowflake:
* Dimensional/Kimball: This is a popular dimensional data model that uses a star or snowflake schema to organize data into fact and dimension tables. Fact tables store quantitative measures and foreign keys to dimension tables. Dimension tables store descriptive attributes and hierarchies. A star schema has a single denormalized dimension table for each dimension, while a snowflake schema has multiple normalized dimension tables for each dimension. Snowflake supports both star and snowflake schemas, and allows users to create views and joins to simplify queries.
* Inmon/3NF: This is a common normalized data model that uses a third normal form (3NF) schema to organize data into entities and relationships. 3NF schema eliminates data duplication and ensures data consistency by applying three rules: 1) every column in a table must depend on the primary key, 2)
* every column in a table must depend on the whole primary key, not a part of it, and 3) every column in a table must depend only on the primary key, not on other columns. Snowflake supports 3NF schema and allows users to create referential integrity constraints and foreign key relationships to enforce data quality.
* Data vault: This is a hybrid data model that combines the best practices of dimensional and normalized data models to create a scalable, flexible, and resilient data warehouse. Data vault schema consists of three types of tables: hubs, links, and satellites. Hubs store business keys and metadata for each entity.
Links store associations and relationships between entities. Satellites store descriptive attributes and historical changes for each entity or relationship. Snowflake supports data vault schema and allows users to leverage its features such as time travel, zero-copy cloning, and secure data sharing to implement data vault methodology.
References: What is Data Modeling? | Snowflake, Snowflake Schema in Data Warehouse Model - GeeksforGeeks, [Data Vault 2.0 Modeling with Snowflake]
NEW QUESTION # 59
A Data Engineer is designing a near real-time ingestion pipeline for a retail company to ingest event logs into Snowflake to derive insights. A Snowflake Architect is asked to define security best practices to configure access control privileges for the data load for auto-ingest to Snowpipe.
What are the MINIMUM object privileges required for the Snowpipe user to execute Snowpipe?
- A. OWNERSHIP on the named pipe, USAGE on the named stage, target database, and schema, and INSERT and SELECT on the target table
- B. OWNERSHIP on the named pipe, USAGE and READ on the named stage, USAGE on the target database and schema, and INSERT end SELECT on the target table
- C. CREATE on the named pipe, USAGE and READ on the named stage, USAGE on the target database and schema, and INSERT end SELECT on the target table
- D. USAGE on the named pipe, named stage, target database, and schema, and INSERT and SELECT on the target table
Answer: B
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the minimum object privileges required for the Snowpipe user to execute Snowpipe are:
* OWNERSHIP on the named pipe. This privilege allows the Snowpipe user to create, modify, and drop the pipe object that defines the COPY statement for loading data from the stage to the table1.
* USAGE and READ on the named stage. These privileges allow the Snowpipe user to access and read the data files from the stage that are loaded by Snowpipe2.
* USAGE on the target database and schema. These privileges allow the Snowpipe user to access the database and schema that contain the target table3.
* INSERT and SELECT on the target table. These privileges allow the Snowpipe user to insert data into the table and select data from the table4.
The other options are incorrect because they do not specify the minimum object privileges required for the Snowpipe user to execute Snowpipe. Option A is incorrect because it does not include the READ privilege on the named stage, which is required for the Snowpipe user to read the data files from the stage. Option C is incorrect because it does not include the OWNERSHIP privilege on the named pipe, which is required for the Snowpipe user to create, modify, and drop the pipe object. Option D is incorrect because it does not include the OWNERSHIP privilege on the named pipe or the READ privilege on the named stage, which are both required for the Snowpipe user to execute Snowpipe. References: CREATE PIPE | Snowflake Documentation, CREATE STAGE | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation, CREATE TABLE | Snowflake Documentation
NEW QUESTION # 60
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