Snowflake ARA-C01 Exam With Confidence Using Practice Dumps

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 .

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]

 A masking policy is a feature of Snowflake that allows masking sensitive data in query results based on the role of the user and the condition of the data. A masking policy can be applied to a column in a table or a view, and it can use another column in the same table or view as a conditional column. A conditional column is a column that determines whether the masking policy is applied or not based on its value1.

In this case, the requirement can be met by using a masking policy on the username column with event_timestamp as a conditional column. The masking policy can use a function that masks the username if the event_timestamp is older than six months based on the current date, and returns the original username otherwise. The masking policy canbe applied to the user_events table, and it will also be applied when creating views using the table or cloning the table2.

The other options are not correct because:

A. Using a masking policy on the username column using an entitlement table with valid dates would require creating another table that stores the valid dates for each username, and joining it with the user_events table in the masking policy function. This would add complexity and overhead to the masking policy, and it would not use the event_timestamp column as the condition for masking.

B. Using a row level policy on the user_events table using an entitlement table with valid dates would require creating another table that stores the valid dates for each username, and joining it with the user_events table in the row access policy function. This would filter out the rows that have event_timestamp older than six months based on the valid dates, instead of masking the username column. This would not meet the requirement of masking the username, and it would also reduce the visibility of the event data.

D. Using a secure view on the user_events table using a case statement on the username column would require creating a view that uses a case expression to mask the username column based on the event_timestamp column. This would meet the requirement of masking the username, but it would not be applied when cloning the table. A secure view is a view that prevents the underlying data from being exposed by queries on the view. However, a secure view does not prevent the underlying data from being exposed by cloning the table3.

1: Masking Policies | Snowflake Documentation

2: Using Conditional Columns in Masking Policies | Snowflake Documentation

3: Secure Views | Snowflake Documentation

 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