These two actions are possible with an inbound share, according to the Snowflake documentation and the web search results. An inbound share is a share that is created by another Snowflake account (the provider) and imported into your account (the consumer). An inbound share allows you to access the data shared by the provider, but not to modify or delete it. However, you can perform some actions with the inbound share, such as:
* Clone a table from a share. You can create a copy of a table from an inbound share using the CREATE TABLE ... CLONE statement. The clone will contain the same data and metadata as the original table,
* but it will be independent of the share. You can modify or delete the clone as you wish, but it will not reflect any changes made to the original table by the provider1.
* Create additional views inside the shared database. You can create views on the tables or views from an inbound share using the CREATE VIEW statement. The views will be stored in the shared database, but they will be owned by your account. You can query the views as you would query any other view in your account, but you cannot modify or delete the underlying objects from the share2.
The other actions listed are not possible with an inbound share, because they would require modifying the share or the shared objects, which are read-only for the consumer. You cannot grant modify permissions on the share, create a table from the shared database, or create a table stream on the shared table34.
References:
* Cloning Objects from a Share | Snowflake Documentation
* Creating Views on Shared Data | Snowflake Documentation
* Importing Data from a Share | Snowflake Documentation
* Streams on Shared Tables | Snowflake Documentation

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. References: 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

Comprehensive and Detailed Explanation From Exact Extract:
Snowflake supports both implicit and explicit transactions. However, only specific statement types are allowed within transactions.
Option C:
This is correct. In Snowflake, transactions can be started with any of the following: BEGIN, BEGIN WORK, or START TRANSACTION. Transactions can be ended using COMMIT, COMMIT WORK, or ROLLBACK.
Official Extract:
"You can explicitly start a transaction using the BEGIN, BEGIN WORK, or START TRANSACTION statements and end it using the COMMIT, COMMIT WORK, or ROLLBACK statements." Source:Snowflake SQL Transactions Option E:
This is correct. Transactions should only include DML statements (INSERT, UPDATE, DELETE, MERGE) and queries. DDL statements (CREATE, ALTER, DROP) automatically commit and cannot be part of an explicit transaction block.
Official Extract:
"A transaction can contain only DML statements and queries. Any DDL statement implicitly commits the current transaction." Source:Snowflake SQL Transactions Option A:
Incorrect. DDL statements are not allowed inside explicit transactions. If used, they trigger an implicit commit.
Option B:
Incorrect. The autocommit setting cannot be modified within a stored procedure. Autocommit is session-level and not dynamically changeable within procedural logic.
Option D:
Incorrect. Snowflake does not support END TRANSACTION as a valid SQL command. The correct ending statement for a transaction is COMMIT or ROLLBACK.
References:
Snowflake Documentation: Transactions
COMMIT / ROLLBACK Commands
SnowPro Advanced Study Guide - SQL Semantics and Transaction Management

Snowflake context functions are functions that return information about the current session, user, role, warehouse, database, schema, or object. They can be used to help determine whether a user is authorized to see data that has column-level security enforced by setting masking policy conditions based on the context functions. The following context functions are relevant for column-level security:
current_role: This function returns the name of the role in use for the current session. It can be used to set masking policy conditions that target the current session and are not affected by the execution context of the SQL statement. For example, a masking policy condition using current_role can allow or deny access to a column based on the role that the user activated in the session.
invoker_role: This function returns the name of the executing role in a SQL statement. It can be used to set masking policy conditions that target the executing role and are affected by the execution context of the SQL statement. For example, a masking policy condition using invoker_role can allow or deny access to a column based on the role that the user specified in the SQL statement, such as using the AS ROLE clause or a stored procedure.
is_role_in_session: This function returns TRUE if the user's current role in the session (i.e. the role returned by current_role) inherits the privileges of the specified role. It can be used to set masking policy conditions that involve role hierarchy and privilege inheritance. For example, a masking policy condition using is_role_in_session can allow or deny access to a column based on whether the user's current role is a lower privilege role in the specified role hierarchy.
The other options are not valid ways to use the Snowflake context functions for column-level security:
Set masking policy conditions using is_role_in_session targeting the role in use for the current account. This option is incorrect because is_role_in_session does not target the role in use for the current account, but rather the role in use for the current session. Also, the current account is not a role, but rather a logical entity that contains users, roles, warehouses, databases, and other objects.
Determine if there are ownership privileges on the masking policy that would allow the use of any function. This option is incorrect because ownership privileges on the masking policy do not affect the use of any function, but rather the ability to create, alter, or drop the masking policy. Also, this is not a way to use the Snowflake context functions, but rather a way to check the privileges on the masking policy object.
Assign the accountadmin role to the user who is executing the object. This option is incorrect because assigning the accountadmin role to the user who is executing the object does not involve using the Snowflake context functions, but rather granting the highest-level role to the user. Also, this is not a recommended practice for column-level security, as it would give the user full access to all objects and data in the account, which could compromise data security and governance.
Reference:
Context Functions
Advanced Column-level Security topics
Snowflake Data Governance: Column Level Security Overview
Data Security Snowflake Part 2 - Column Level Security