By default, Snowflake does not allow sharing data from a Business Critical edition to a non-Business Critical edition. This is because Business Critical edition provides enhanced security and data protection features that are not available in lower editions. However, this restriction can be overridden by setting the share_restriction parameter on the shared object (database, schema, or table) to false. This parameter allows the data provider to explicitly allow sharing data with lower edition accounts. Note that this parameter can only be set by the data provider, not the data consumer. Also, setting this parameter to false may reduce the level of security and data protection for the shared data.
Enable Data Share:Business Critical Account to Lower Edition
Sharing Is Not Allowed From An Account on BUSINESS CRITICAL Edition to an Account On A Lower Edition SQL Execution Error: Sharing is Not Allowed from an Account on BUSINESS CRITICAL Edition to an Account on a Lower Edition Snowflake Editions | Snowflake Documentation

A: Snowflake's transactions can indeed include DDL (Data Definition Language), DML (Data Manipulation Language), and query statements. When executed within a transaction block, they all contribute to the atomicity of the transaction-either all of them commit together or none at all.C. Snowflake supports explicit transaction control through the use of the BEGIN TRANSACTION (or simply BEGIN) and COMMIT statements. Alternatively, the BEGIN WORK and COMMIT WORK syntax is also supported, which is a standard SQL syntax for initiating and ending transactions, respectively.Note: The END TRANSACTION statement is not used in Snowflake to end a transaction; the correct statement is COMMIT or COMMIT WORK.

This is the best practice recommendation for the order of priority when applications authenticate to Snowflake, according to the Snowflake documentation and the web search results. Authentication is the process of verifying the identity of a user or application that connects to Snowflake. Snowflake supports multiple authentication methods, each with different advantages and disadvantages. The recommended order of priority is based on the following factors:
Security: The authentication method should provide a high level of security and protection against unauthorized access or data breaches. The authentication method should also support multi-factor authentication (MFA) or single sign-on (SSO) for additional security.
Convenience: The authentication method should provide a smooth and easy user experience, without requiring complex or manual steps. The authentication method should also support seamless integration with external identity providers or applications.
Flexibility: The authentication method should provide a range of options and features to suit different use cases and scenarios. The authentication method should also support customization and configuration to meet specific requirements.
Based on these factors, the recommended order of priority is:
OAuth (either Snowflake OAuth or External OAuth): OAuth is an open standard for authorization that allows applications to access Snowflake resources on behalf of a user, without exposing the user's credentials. OAuth provides a high level of security, convenience, and flexibility, as it supports MFA, SSO, token-based authentication, and various grant types and scopes. OAuth can be implemented using either Snowflake OAuth or External OAuth, depending on the identity provider and the application12.
External browser: External browser is an authentication method that allows users to log in to Snowflake using a web browser and an external identity provider, such as Okta, Azure AD, or Ping Identity. External browser provides a high level of security and convenience, as it supports MFA, SSO, and federated authentication. External browser also provides a consistent user interface and experience across different platforms and devices34.
Okta native authentication: Okta native authentication is an authentication method that allows users to log in to Snowflake using Okta as the identity provider, without using a web browser. Okta native authentication provides a high level of security and convenience, as it supports MFA, SSO, and federated authentication. Okta native authentication also provides a native user interface and experience for Okta users, and supports various Okta features, such as password policies and user management56.
Key Pair Authentication: Key Pair Authentication is an authentication method that allows users to log in to Snowflake using a public-private key pair, without using a password. Key Pair Authentication provides a high level of security, as it relies on asymmetric encryption and digital signatures. Key Pair Authentication also provides a flexible and customizable authentication option, as it supports various key formats, algorithms, and expiration times. Key Pair Authentication is mostly used for service account users, such as applications or scripts that connect to Snowflake programmatically7 .
Password: Password is the simplest and most basic authentication method that allows users to log in to Snowflake using a username and password. Password provides a low level of security, as it relies on symmetric encryption and is vulnerable to brute force attacks or phishing. Password also provides a low level of convenience and flexibility, as it requires manual input and management, and does not support MFA or SSO. Password is the least recommended authentication method, and should be used only as a last resort or for testing purposes .
Reference:
Snowflake Documentation: Snowflake OAuth
Snowflake Documentation: External OAuth
Snowflake Documentation: External Browser Authentication
Snowflake Blog: How to Use External Browser Authentication with Snowflake Snowflake Documentation: Okta Native Authentication Snowflake Blog: How to Use Okta Native Authentication with Snowflake Snowflake Documentation: Key Pair Authentication
[Snowflake Blog: How to Use Key Pair Authentication with Snowflake]
[Snowflake Documentation: Password Authentication]
[Snowflake Blog: How to Use Password Authentication with Snowflake]

According to the Snowflake documentation, the following are some considerations for choosing clustering for a table1:
* Clustering is optimal when either:
* You require the fastest possible response times, regardless of cost.
* Your improved query performance offsets the credits required to cluster and maintain the table.
* Clustering is most effective when the clustering key is used in the following types of query predicates:
* Filter predicates (e.g. WHERE clauses)
* Join predicates (e.g. ON clauses)
* Grouping predicates (e.g. GROUP BY clauses)
* Sorting predicates (e.g. ORDER BY clauses)
* Clustering is less effective when the clustering key is not used in any of the above query predicates, or when the clustering key is used in a predicate that requires a function or expression to be applied to the key (e.g. DATE_TRUNC, TO_CHAR, etc.).
* For most tables, Snowflake recommends a maximum of 3 or 4 columns (or expressions) per key.
Adding more than 3-4 columns tends to increase costs more than benefits.
Based on these considerations, the best option for the clustering key columns is C. C1, C3, C2, because:
* These columns are heavily used in filter and join conditions of SELECT queries, which are the most effective types of predicates for clustering.
* These columns have high cardinality, which means they have many distinct values and can help reduce the clustering skew and improve the compression ratio.
* These columns are likely to be correlated with each other, which means they can help co-locate similar rows in the same micro-partitions and improve the scan efficiency.
* These columns do not require any functions or expressions to be applied to them, which means they can be directly used in the predicates without affecting the clustering.
References: 1: Considerations for Choosing Clustering for a Table | Snowflake Documentation

Compilation time is the time it takes for the optimizer to create an optimal query plan for the efficient execution of the query. It also involves some pruning of partition files, making the query execution efficient2 If the compilation time is greater than the execution time, it means that the optimizer spent more time analyzing the query than actually running it. This could indicate that the query has overly complex logic, such as multiple joins, subqueries, aggregations, or expressions. The complexity of the query could also affect the size and quality of the query plan, which could impact the performance of the query3 To reduce the compilation time, the Architect can try to simplify the query logic, use views or common table expressions (CTEs) to break down the query into smaller parts, or use hints to guide the optimizer. The Architect can also use the EXPLAIN command to examine the query plan and identify potential bottlenecks or inefficiencies4 Reference:
1: SnowPro Advanced: Architect | Study Guide 5
2: Snowflake Documentation | Query Profile Overview 6
3: Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time 7
4: Snowflake Documentation | Optimizing Query Performance 8
5: SnowPro Advanced: Architect | Study Guide
6: Query Profile Overview
7: Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time
8: Optimizing Query Performance