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NEW QUESTION # 77
A user can change object parameters using which of the following roles?
- A. ACCOUNTADMIN, USER with PRIVILEGE
- B. SECURITYADMIN, USER with PRIVILEGE
- C. SYSADMIN, SECURITYADMIN
- D. ACCOUNTADMIN, SECURITYADMIN
Answer: A
Explanation:
According to the Snowflake documentation, object parameters are parameters that can be set on individual objects such as databases, schemas, tables, and stages. Object parameters can be set by users with the appropriate privileges on the objects. For example, to set the object parameter AUTO_REFRESH on a table, the user must have the MODIFY privilege on the table. The ACCOUNTADMIN role has the highest level of privileges on all objects in the account, so it can set any object parameter on any object. However, other roles, such as SECURITYADMIN or SYSADMIN, do not have the same level of privileges on all objects, so they cannot set object parameters on objects they do not own or have the required privileges on. Therefore, the correct answer is C. ACCOUNTADMIN, USER with PRIVILEGE.
Reference:
Parameters | Snowflake Documentation
Object Parameters | Snowflake Documentation
Object Privileges | Snowflake Documentation
NEW QUESTION # 78
When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)
- A. JSON
- B. CSV
- C. XML
- D. Avro
- E. Parquet
Answer: A,D
Explanation:
The data formats that are supported for the messages when using the Snowflake Connector for Kafka are Avro and JSON. These are the two formats that the connector can parse and convert into Snowflake table rows. The connector supports both schemaless and schematized JSON, as well as Avro with or without a schema registry1. The other options are incorrect because they are not supported data formats for the messages. CSV, XML, and Parquet are not formats that the connector can parse and convert into Snowflake table rows. If the messages are in these formats, the connector will load them as VARIANT data type and store them as raw strings in the table2. Reference: Snowflake Connector for Kafka | Snowflake Documentation, Loading Protobuf Data using the Snowflake Connector for Kafka | Snowflake Documentation
NEW QUESTION # 79
Snowflake recommends starting slowly with SEARCH OPTIMIZATION(i.e. adding search optimization to only a few tables at first) and closely monitoring the costs and benefits.
- A. TRUE
- B. FALSE
Answer: A
NEW QUESTION # 80
A Snowflake Architect is setting up database replication to support a disaster recovery plan. The primary database has external tables.
How should the database be replicated?
- A. Create a clone of the primary database then replicate the database.
- B. Share the primary database with an account in the same region that the database will be replicated to.
- C. Move the external tables to a database that is not replicated, then replicate the primary database.
- D. Replicate the database ensuring the replicated database is in the same region as the external tables.
Answer: C
Explanation:
Database replication is a feature that allows you to create a copy of a database in another account, region, or cloud platform for disaster recovery or business continuity purposes. However, not all database objects can be replicated. External tables are one of the exceptions, as they reference data files stored in an external stage that is not part of Snowflake. Therefore, to replicate a database that contains external tables, you need to move the external tables to a separate database that is not replicated, and then replicate the primary database that contains the other objects. This way, you can avoid replication errors and ensure consistency between the primary and secondary databases. The other options are incorrect because they either do not address the issue of external tables, or they use an alternative method that is not supported by Snowflake. You cannot create a clone of the primary database and then replicate it, as replication only works on the original database, not on its clones. You also cannot share the primary database with another account, as sharing is a different feature that does not create a copy of the database, but rather grants access to the shared objects. Finally, you do not need to ensure that the replicated database is in the same region as the external tables, as external tables can access data files stored in any region or cloud platform, as long as the stage URL is valid and accessible. References:
* [Replication and Failover/Failback] 1
* [Introduction to External Tables] 2
* [Working with External Tables] 3
* [Replication : How to migrate an account from One Cloud Platform or Region to another in
* Snowflake] 4
NEW QUESTION # 81
What transformations are supported in the below SQL statement? (Select THREE).
CREATE PIPE ... AS COPY ... FROM (...)
- A. Data can be filtered by an optional where clause.
- B. Type casts are supported.
- C. Incoming data can be joined with other tables.
- D. Columns can be omitted.
- E. The ON ERROR - ABORT statement command can be used.
- F. Columns can be reordered.
Answer: A,D,F
Explanation:
* The SQL statement is a command for creating a pipe in Snowflake, which is an object that defines the COPY INTO <table> statement used by Snowpipe to load data from an ingestion queue into tables1. The statement uses a subquery in the FROM clause to transform the data from the staged files before loading it into the table2.
* The transformations supported in the subquery are as follows2:
* Data can be filtered by an optional WHERE clause, which specifies a condition that must be satisfied by the rows returned by the subquery. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable
from (
select * from @mystage
where col1 = 'A' and col2 > 10
);
* Columns can be reordered, which means changing the order of the columns in the subquery to match the order of the columns in the target table. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2, col3)
from (
select col3, col1, col2 from @mystage
);
* Columns can be omitted, which means excluding some columns from the subquery that are not needed in the target table. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2)
from (
select col1, col2 from @mystage
);
* The other options are not supported in the subquery because2:
* Type casts are not supported, which means changing the data type of a column in the subquery.
For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2)
from (
select col1::date, col2 from @mystage
);
* Incoming data can not be joined with other tables, which means combining the data from the staged files with the data from another table in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2, col3)
from (
select s.col1, s.col2, t.col3 from @mystage s
join othertable t on s.col1 = t.col1
);
* The ON ERROR - ABORT statement command can not be used, which means aborting the entire load operation if any error occurs. This command can only be used in the COPY INTO <table> statement, not in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable
from (
select * from @mystage
on error abort
);
References:
* 1: CREATE PIPE | Snowflake Documentation
* 2: Transforming Data During a Load | Snowflake Documentation
NEW QUESTION # 82
Company A has recently acquired company B. The Snowflake deployment for company B is located in the Azure West Europe region.
As part of the integration process, an Architect has been asked to consolidate company B's sales data into company A's Snowflake account which is located in the AWS us-east-1 region.
How can this requirement be met?
- A. Replicate the sales data from company B's Snowflake account into company A's Snowflake account using cross-region data replication within Snowflake. Configure a direct share from company B's account to company A's account.
- B. Export the sales data from company B's Snowflake account as CSV files, and transfer the files to company A's Snowflake account. Import the data using Snowflake's data loading capabilities.
- C. Migrate company B's Snowflake deployment to the same region as company A's Snowflake deployment, ensuring data locality. Then perform a direct database-to-database merge of the sales data.
- D. Build a custom data pipeline using Azure Data Factory or a similar tool to extract the sales data from company B's Snowflake account. Transform the data, then load it into company A's Snowflake account.
Answer: C
NEW QUESTION # 83
Which of the following ingestion methods can be used to load near real-time data by using the messaging services provided by a cloud provider?
- A. Snowflake streams
- B. Spark
- C. Snowflake Connector for Kafka
- D. Snowpipe
Answer: C,D
Explanation:
Snowflake Connector for Kafka and Snowpipe are two ingestion methods that can be used to load near real-time data by using the messaging services provided by a cloud provider. Snowflake Connector for Kafka enables you to stream structured and semi-structured data from Apache Kafka topics into Snowflake tables. Snowpipe enables you to load data from files that are continuously added to a cloud storage location, such as Amazon S3 or Azure Blob Storage. Both methods leverage Snowflake's micro-partitioning and columnar storage to optimize data ingestion and query performance. Snowflake streams and Spark are not ingestion methods, but rather components of the Snowflake architecture. Snowflake streams provide change data capture (CDC) functionality by tracking data changes in a table. Spark is a distributed computing framework that can be used to process large-scale data and write it to Snowflake using the Snowflake Spark Connector. Reference:
Snowflake Connector for Kafka
Snowpipe
Snowflake Streams
Snowflake Spark Connector
NEW QUESTION # 84
An Architect is designing a data lake with Snowflake. The company has structured, semi-structured, and unstructured data. The company wants to save the data inside the data lake within the Snowflake system. The company is planning on sharing data among its corporate branches using Snowflake data sharing.
What should be considered when sharing the unstructured data within Snowflake?
- A. A scoped URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 24-hour time limit for the URL.
- B. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with the "expiration_time" argument defined for the URL time limit.
- C. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 7-day time limit for the URL.
- D. A pre-signed URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with no time limit for the URL.
Answer: A
Explanation:
When sharing unstructured data within Snowflake, using a scoped URL is recommended. Scoped URLs provide temporary access to staged files without granting privileges to the stage itself, enhancing security. The URL expires when the persisted query result period ends, which is currently set to 24 hours. This approach is suitable for sharing unstructured data over secure views within Snowflake's data sharing framework.
References: The answer is based on Snowflake's official documentation regarding the sharing of unstructured data and the use of scoped URLs1.
NEW QUESTION # 85
Which security, governance, and data protection features require, at a MINIMUM, the Business Critical edition of Snowflake? (Choose two.)
- A. Customer-managed encryption keys through Tri-Secret Secure
- B. AWS, Azure, or Google Cloud private connectivity to Snowflake
- C. Extended Time Travel (up to 90 days)
- D. Federated authentication and SSO
- E. Periodic rekeying of encrypted data
Answer: A,B
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the security, governance, and data protection features that require, at a minimum, the Business Critical edition of Snowflake are:
* Customer-managed encryption keys through Tri-Secret Secure. This feature allows customers to manage their own encryption keys for data at rest in Snowflake, using a combination of three secrets: a master key, a service key, and a security password. This provides an additional layer of security and control over the data encryption and decryption process1.
* Periodic rekeying of encrypted data. This feature allows customers to periodically rotate the encryption keys for data at rest in Snowflake, using either Snowflake-managed keys or customer-managed keys. This enhances the security and protection of the data by reducing the risk of key compromise or exposure2.
The other options are incorrect because they do not require the Business Critical edition of Snowflake. Option A is incorrect because extended Time Travel (up to 90 days) is available with the Enterprise edition of Snowflake3. Option D is incorrect because AWS, Azure, or Google Cloud private connectivity to Snowflake is available with the Standard edition of Snowflake4. Option E is incorrect because federated authentication and SSO are available with the Standard edition of Snowflake5. References: Tri-Secret Secure | Snowflake Documentation, Periodic Rekeying of Encrypted Data | Snowflake Documentation, Snowflake Editions | Snowflake Documentation, Snowflake Network Policies | Snowflake Documentation, Configuring Federated Authentication and SSO | Snowflake Documentation
NEW QUESTION # 86
Which of the following ingestion methods can be used to load near real-time data by using the messaging services provided by a cloud provider?
- A. Snowflake streams
- B. Spark
- C. Snowflake Connector for Kafka
- D. Snowpipe
Answer: C,D
Explanation:
Snowflake Connector for Kafka and Snowpipe are two ingestion methods that can be used to load near real-time data by using the messaging services provided by a cloud provider. Snowflake Connector for Kafka enables you to stream structured and semi-structured data from Apache Kafka topics into Snowflake tables.
Snowpipe enables you to load data from files that are continuously added to a cloud storage location, such as Amazon S3 or Azure Blob Storage. Both methods leverage Snowflake's micro-partitioning and columnar storage to optimize data ingestion and query performance. Snowflake streams and Spark are not ingestion methods, but rather components of the Snowflake architecture. Snowflake streams provide change data capture (CDC) functionality by tracking data changes in a table. Spark is a distributed computing framework that can be used to process large-scale data and write it to Snowflake using the Snowflake Spark Connector. References:
* Snowflake Connector for Kafka
* Snowpipe
* Snowflake Streams
* Snowflake Spark Connector
NEW QUESTION # 87
An Architect has a VPN_ACCESS_LOGS table in the SECURITY_LOGS schema containing timestamps of the connection and disconnection, username of the user, and summary statistics.
What should the Architect do to enable the Snowflake search optimization service on this table?
- A. Assume role with ALL PRIVILEGES on VPN_ACCESS_LOGS and ADD SEARCH OPTIMIZATION in the SECURITY_LOGS schema.
- B. Assume role with OWNERSHIP on future tables and ADD SEARCH OPTIMIZATION on the SECURITY_LOGS schema.
- C. Assume role with OWNERSHIP on VPN_ACCESS_LOGS and ADD SEARCH OPTIMIZATION in the SECURITY_LOGS schema.
- D. Assume role with ALL PRIVILEGES including ADD SEARCH OPTIMIZATION in the SECURITY LOGS schema.
Answer: C
Explanation:
Explanation
According to the SnowPro Advanced: Architect Exam Study Guide, to enable the search optimization service on a table, the user must have the ADD SEARCH OPTIMIZATION privilege on the table and the schema.
The privilege can be granted explicitly or inherited from a higher-level object, such as a database or a role. The OWNERSHIP privilege on a table implies the ADD SEARCH OPTIMIZATION privilege, so the user who owns the table can enable the search optimization service on it. Therefore, the correct answer is to assume a role with OWNERSHIP on VPN_ACCESS_LOGS and ADD SEARCH OPTIMIZATION in the SECURITY_LOGS schema. This will allow the user to enable the search optimization service on the VPN_ACCESS_LOGS table and any future tables created in the SECURITY_LOGS schema. The other options are incorrect because they either grant excessive privileges or do not grant the required privileges on the table or the schema. References:
* SnowPro Advanced: Architect Exam Study Guide, page 11, section 2.3.1
* Snowflake Documentation: Enabling the Search Optimization Service
NEW QUESTION # 88
You are a snowflake architect in an organization. The business team came to to deploy an use case which requires you to load some data which they can visualize through tableau. Everyday new data comes in and the old data is no longer required.
What type of table you will use in this case to optimize cost
- A. PERMANENT
- B. TRANSIENT
- C. TEMPORARY
Answer: B
NEW QUESTION # 89
An Architect clones a database and all of its objects, including tasks. After the cloning, the tasks stop running.
Why is this occurring?
- A. The Architect has insufficient privileges to alter tasks on the cloned database.
- B. Tasks cannot be cloned.
- C. The objects that the tasks reference are not fully qualified.
- D. Cloned tasks are suspended by default and must be manually resumed.
Answer: D
Explanation:
When a database is cloned, all of its objects, including tasks, are also cloned. However, cloned tasks are suspended by default and must be manually resumed by using the ALTER TASK command. This is to prevent the cloned tasks from running unexpectedly or interfering with the original tasks. Therefore, the reason why the tasks stop running after the cloning is because they are suspended by default (Option C). Options A, B, and D are not correct because tasks can be cloned, the objects that the tasks reference are also cloned and do not need to be fully qualified, and the Architect does not need to alter the tasks on the cloned database, only resume them. Reference: The answer can be verified from Snowflake's official documentation on cloning and tasks available on their website. Here are some relevant links:
Cloning Objects | Snowflake Documentation
Tasks | Snowflake Documentation
ALTER TASK | Snowflake Documentation
NEW QUESTION # 90
Dynamic data masking is supported in which editions of snowflake
- A. VPS
- B. Business Critical
- C. Standard
- D. Enterprise
Answer: A,B,D
NEW QUESTION # 91
You have created a table as below
CREATE TABLE SNOWFLAKE (FLAKE_ID INTEGER, UDEMY_COURSE VARCHAR);
Which of the below select query will fail for this table?
- A. SELECT * from "snowflake";
- B. SELECT * FROM "SNOWFLAKE";
- C. SELECT * from Snowflake;
- D. SELECT * from snowflake;
Answer: A
NEW QUESTION # 92
A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?
- A. Create accounts for each tenant in the Snowflake organization.
- B. Create an object for each tenant strategy if row level security is viable for isolating tenants.
- C. Create an object for each tenant strategy if row level security is not viable for isolating tenants.
- D. Create a multi-tenant table strategy if row level security is not viable for isolating tenants.
Answer: A
Explanation:
Explanation
This approach meets the requirements of strong legal isolation and multi-tenancy. By creating separate accounts for each tenant, the application can ensure that each tenant has its own dedicated storage, compute, and metadata resources, as well as its own encryption keys and security policies. This provides the highest level of isolation and data protection among the tenancy models. Furthermore, by creating the accounts within the same Snowflake organization, the application can leverage the features of Snowflake Organizations, such as centralized billing, account management, and cross-account data sharing.
References:
* Snowflake Organizations Overview | Snowflake Documentation
* Design Patterns for Building Multi-Tenant Applications on Snowflake
NEW QUESTION # 93
A table for IOT devices that measures water usage is created. The table quickly becomes large and contains more than 2 billion rows.
The general query patterns for the table are:
1. DeviceId, lOT_timestamp and Customerld are frequently used in the filter predicate for the select statement
2. The columns City and DeviceManuf acturer are often retrieved
3. There is often a count on Uniqueld
Which field(s) should be used for the clustering key?
- A. Deviceld and Customerld
- B. lOT_timestamp
- C. City and DeviceManuf acturer
- D. Uniqueld
Answer: A
Explanation:
A clustering key is a subset of columns or expressions that are used to co-locate the data in the same micro-partitions, which are the units of storage in Snowflake. Clustering can improve the performance of queries that filter on the clustering key columns, as it reduces the amount of data that needs to be scanned. The best choice for a clustering key depends on the query patterns and the data distribution in the table. In this case, the columns DeviceId, IOT_timestamp, and CustomerId are frequently used in the filter predicate for the select statement, which means they are good candidates for the clustering key. The columns City and DeviceManufacturer are often retrieved, but not filtered on, so they are not as important for the clustering key.
The column UniqueId is used for counting, but it is not a good choice for the clustering key, as it is likely to have a high cardinality and a uniform distribution, which means it will not help to co-locate the data.
Therefore, the best option is to use DeviceId and CustomerId as the clustering key, as they can help to prune the micro-partitions and speed up the queries. References: Clustering Keys & Clustered Tables, Micro-partitions & Data Clustering, A Complete Guide to Snowflake Clustering
NEW QUESTION # 94
Which system functions does Snowflake provide to monitor clustering information within a table (Choose two.)
- A. SYSTEM$CLUSTERING_DEPTH
- B. SYSTEM$CLUSTERING_PERCENT
- C. SYSTEM$CLUSTERING_KEYS
- D. SYSTEM$CLUSTERING_INFORMATION
- E. SYSTEM$CLUSTERING_USAGE
Answer: A,D
NEW QUESTION # 95
An Architect uses COPY INTO with the ON_ERROR=SKIP_FILE option to bulk load CSV files into a table called TABLEA, using its table stage. One file named file5.csv fails to load. The Architect fixes the file and re-loads it to the stage with the exact same file name it had previously.
Which commands should the Architect use to load only file5.csv file from the stage? (Choose two.)
- A. COPY INTO tablea FROM @%tablea MERGE = TRUE;
- B. COPY INTO tablea FROM @%tablea FORCE = TRUE;
- C. COPY INTO tablea FROM @%tablea NEW_FILES_ONLY = TRUE;
- D. COPY INTO tablea FROM @%tablea FILES = ('file5.csv');
- E. COPY INTO tablea FROM @%tablea RETURN_FAILED_ONLY = TRUE;
- F. COPY INTO tablea FROM @%tablea;
Answer: C,F
NEW QUESTION # 96
A large manufacturing company runs a dozen individual Snowflake accounts across its business divisions. The company wants to increase the level of data sharing to support supply chain optimizations and increase its purchasing leverage with multiple vendors.
The company's Snowflake Architects need to design a solution that would allow the business divisions to decide what to share, while minimizing the level of effort spent on configuration and management. Most of the company divisions use Snowflake accounts in the same cloud deployments with a few exceptions for European-based divisions.
According to Snowflake recommended best practice, how should these requirements be met?
- A. Migrate the European accounts in the global region and manage shares in a connected graph architecture. Deploy a Data Exchange.
- B. Deploy to the Snowflake Marketplace making sure that invoker_share() is used in all secure views.
- C. Deploy a Private Data Exchange in combination with data shares for the European accounts.
- D. Deploy a Private Data Exchange and use replication to allow European data shares in the Exchange.
Answer: C
Explanation:
According to Snowflake recommended best practice, the requirements of the large manufacturing company should be met by deploying a Private Data Exchange in combination with data shares for the European accounts. A Private Data Exchange is a feature of the Snowflake Data Cloud platform that enables secure and governed sharing of data between organizations. It allows Snowflake customers to create their own data hub and invite other parts of their organization or external partners to access and contribute data sets. A Private Data Exchange provides centralized management, granular access control, and data usage metrics for the data shared in the exchange1. A data share is a secure and direct way of sharing data between Snowflake accounts without having to copy or move the data. A data share allows the data provider to grant privileges on selected objects in their account to one or more data consumers in other accounts2. By using a Private Data Exchange in combination with data shares, the company can achieve the following benefits:
The business divisions can decide what data to share and publish it to the Private Data Exchange, where it can be discovered and accessed by other members of the exchange. This reduces the effort and complexity of managing multiple data sharing relationships and configurations.
The company can leverage the existing Snowflake accounts in the same cloud deployments to create the Private Data Exchange and invite the members to join. This minimizes the migration and setup costs and leverages the existing Snowflake features and security.
The company can use data shares to share data with the European accounts that are in different regions or cloud platforms. This allows the company to comply with the regional and regulatory requirements for data sovereignty and privacy, while still enabling data collaboration across the organization.
The company can use the Snowflake Data Cloud platform to perform data analysis and transformation on the shared data, as well as integrate with other data sources and applications. This enables the company to optimize its supply chain and increase its purchasing leverage with multiple vendors.
The other options are incorrect because they do not meet the requirements or follow the best practices. Option A is incorrect because migrating the European accounts to the global region may violate the data sovereignty and privacy regulations, and deploying a Data Exchange may not provide the level of control and management that the company needs. Option C is incorrect because deploying to the Snowflake Marketplace may expose the company's data to unwanted consumers, and using invoker_share() in secure views may not provide the desired level of security and governance. Option D is incorrect because using replication to allow European data shares in the Exchange may incur additional costs and complexity, and may not be necessary if data shares can be used instead. Reference: Private Data Exchange | Snowflake Documentation, Introduction to Secure Data Sharing | Snowflake Documentation
NEW QUESTION # 97
Which statements describe characteristics of the use of materialized views in Snowflake? (Choose two.)
- A. They can include ORDER BY clauses.
- B. They cannot include nested subqueries.
- C. They can include context functions, such as CURRENT_TIME().
- D. They can support MIN and MAX aggregates.
- E. They can support inner joins, but not outer joins.
Answer: B,D
Explanation:
Explanation
According to the Snowflake documentation, materialized views have some limitations on the query specification that defines them. One of these limitations is that they cannot include nested subqueries, such as subqueries in the FROM clause or scalar subqueries in the SELECT list. Another limitation is that they cannot include ORDER BY clauses, context functions (such as CURRENT_TIME()), or outer joins. However, materialized views can support MIN and MAX aggregates, as well as other aggregate functions, such as SUM, COUNT, and AVG.
References:
* Limitations on Creating Materialized Views | Snowflake Documentation
* Working with Materialized Views | Snowflake Documentation
NEW QUESTION # 98
......
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