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Snowflake ARA-C01 exam is a rigorous assessment of an individual's technical abilities and understanding of Snowflake's architecture. ARA-C01 exam consists of multiple-choice questions and covers a broad range of topics, including data modeling, security, performance tuning, and integration with other systems. ARA-C01 exam also tests an individual's ability to design and implement advanced Snowflake solutions that meet specific business requirements.

Achieving the Snowflake ARA-C01 Certification demonstrates a high level of expertise in Snowflake's cloud-based data warehousing solutions. It is a valuable credential that can help professionals stand out in the job market and advance their careers in the field of data warehousing and cloud computing.

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q161-Q166):

NEW QUESTION # 161
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. TEMPORARY
C. TRANSIENT

Answer: C

Explanation:
* A transient table is a type of table in Snowflake that does not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. Transient tables are suitable for temporary or intermediate data that can be easily reproduced or replicated1.
* A temporary table is a type of table in Snowflake that is automatically dropped when the session ends or the current user logs out. Temporary tables do not incur any storage costs, but they are not visible to other users or sessions2.
* A permanent table is a type of table in Snowflake that has a Fail-safe period and a Time Travel retention period of up to 90 days. Permanent tables are suitable for persistent and durable data that needs to be protected from accidental or malicious deletion3.
* In this case, the use case requires loading some data that can be visualized through Tableau. The data is updated every day and the old data is no longer required. Therefore, the best type of table to use in this case to optimize cost is a transient table, because it does not incur any Fail-safe costs and it can have a short Time Travel retention period of 0 or 1 day. This way, the data can be loaded and queried by Tableau, and then deleted or overwritten without incurring any unnecessary storage costs.
References: : Transient Tables : Temporary Tables : Understanding & Using Time Travel

NEW QUESTION # 162
At which object type level can the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges be granted?

A. Global
B. Table
C. Database
D. Schema

Answer: A

Explanation:
Explanation
The object type level at which the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges can be granted is global. These are account-level privileges that control who can apply or unset these policies on objects such as columns, tables, views, accounts, or users. These privileges are granted to the ACCOUNTADMIN role by default, and can be granted to other roles as needed.
The other options are incorrect because they are not the object type level at which these privileges can be granted. Database, schema, and table are lower-level object types that do notsupport these privileges. References: Access Control Privileges | Snowflake Documentation, Using Dynamic Data Masking | Snowflake Documentation, Using Row Access Policies | Snowflake Documentation, Using Session Policies | Snowflake Documentation

NEW QUESTION # 163
What are characteristics of Dynamic Data Masking? (Select TWO).

A. A single masking policy can be applied to columns in different tables.
B. The role that creates the masking policy will always see unmasked data In query results
C. A masking policy can be applied to a column with the GEOGRAPHY data type.
D. A masking policy can be applied to the value column of an external table.
E. A masking policy that Is currently set on a table can be dropped.

Answer: A,E

Explanation:
Dynamic Data Masking is a feature that allows masking sensitive data in query results based on the role of the user who executes the query. A masking policy is a user-defined function that specifies the masking logic and can be applied to one or more columns in one or more tables. A masking policy that is currently set on a table can be dropped using the ALTER TABLE command. A single masking policy can be applied to columns in different tables using the ALTER TABLE command with the SET MASKING POLICY clause. The other options are either incorrect or not supported by Snowflake. A masking policy cannot be applied to the value column of an external table, as external tables do not support column-level security. The role that creates the masking policy will not always see unmasked data in query results, as the masking policy can be applied to the owner role as well. A masking policy cannot be applied to a column with the GEOGRAPHY data type, as Snowflake only supports masking policies for scalar data types. Reference: Snowflake Documentation: Dynamic Data Masking, Snowflake Documentation: ALTER TABLE

NEW QUESTION # 164
Which system functions does Snowflake provide to monitor clustering information within a table (Choose two.)

A. SYSTEM$CLUSTERING_PERCENT
B. SYSTEM$CLUSTERING_KEYS
C. SYSTEM$CLUSTERING_INFORMATION
D. SYSTEM$CLUSTERING_USAGE
E. SYSTEM$CLUSTERING_DEPTH

Answer: C,E

Explanation:
According to the Snowflake documentation, these two system functions are provided by Snowflake to monitor clustering information within a table. A system function is a type of function that allows executing actions or returning information about the system. A clustering key is a feature that allows organizing data across micro-partitions based on one or more columns in the table. Clustering can improve query performance by reducing the number of files to scan.
SYSTEM$CLUSTERING_INFORMATION is a system function that returns clustering information, including average clustering depth, for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns a JSON string with the clustering information. The clustering information includes the cluster by keys, the total partition count, the total constant partition count, the average overlaps, and the average depth1.
SYSTEM$CLUSTERING_DEPTH is a system function that returns the clustering depth for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns an integer value with the clustering depth. The clustering depth is the maximum number of overlapping micro-partitions for any micro-partition in the table. A lower clustering depth indicates a better clustering2.
Reference:
SYSTEM$CLUSTERING_INFORMATION | Snowflake Documentation
SYSTEM$CLUSTERING_DEPTH | Snowflake Documentation

NEW QUESTION # 165
Shares are first-class objects in Snowflake for which Snowflake provides a set of DDL commands for creating and managing shares

A. FALSE
B. TRUE

Answer: B

NEW QUESTION # 166
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