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. Reference: 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

* The error message indicates that the schema STAGING does not have time travel data available for the requested timestamp, because the current version of the schema was created on 2021-06-02 23:00:00, which is after the timestamp of 2021-06-01 08:00:00. Therefore, the CLONE statement cannot access
* the historical data of the schema at that point in time.
* Option A is incorrect, because undropping the STAGING schema will not restore the previous version of the schema that was active on 2021-06-01 08:00:00. Instead, it will create a new version of the schema with the same name and no data or objects.
* Option B is incorrect, because modifying the timestamp to 2021-05-01 10:00:00 will not clone the schema as it looked one week ago, but as it looked when it was first created. This may not reflect the desired state of the schema and its objects.
* Option C is correct, because renaming the STAGING schema and performing an UNDROP to retrieve the previous STAGING schema version will restore the schema that was dropped on 2021-06-02
23:00:00. This schema has time travel data available for the requested timestamp of 2021-06-01
08:00:00, and can be cloned using the CLONE statement.
* Option D is incorrect, because cloning can be accomplished by using the UNDROP command to access the previous version of the schema that was active during the proposed time travel period.
References: : Cloning Considerations : Understanding & Using Time Travel : CREATE <object> ... CLONE

This view can be used to query login attempts by Snowflake users within the last 365 days (1 year). It provides information such as the event timestamp, the user name, the client IP, the authentication method, the success or failure status, and the error code or message if the login attempt was unsuccessful. By querying this view, the IT Security team can identify any suspicious or malicious login attempts to Snowflake and take appropriate actions to prevent credential stuffing attacks1. The other options are not the best ways to find recent and ongoing login attempts to Snowflake. Option A is incorrect because the LOGIN_HISTORY Information Schema table function only returns login events within the last 7 days, which may not be sufficient to detect credential stuffing attacks that span a longer period of time2. Option C is incorrect because the History tab in the Snowflake UI only shows the queries executed by the current user or role, not the login events of other users or roles3. Option D is incorrect because the Users section in the Account tab in the Snowflake UI only shows the last login time for each user, not the details of the login attempts or the failures.