SNOWFLAKE ARA-C01 EXAM REAL AND UPDATED DUMPS ARE READY FOR DOWNLOAD

Snowflake ARA-C01 Exam Real and Updated Dumps are Ready for Download

Snowflake ARA-C01 Exam Real and Updated Dumps are Ready for Download

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Snowflake ARA-C01 certification is an advanced-level certification exam that is designed to validate the skills and knowledge of the candidates in the field of Snowflake data warehousing. SnowPro Advanced Architect Certification certification exam is intended for experienced professionals who have a deep understanding of Snowflake architecture, its various components, and their respective functionalities. SnowPro Advanced Architect Certification certification exam is an ideal choice for architects, consultants, and data engineers who work with Snowflake on a daily basis.

To take the Snowflake ARA-C01 Certification Exam, candidates must have already achieved the SnowPro Core Certification, which validates their foundational knowledge of Snowflake. The ARA-C01 exam is designed to test the candidate's ability to apply their knowledge to real-world scenarios and solve complex problems related to Snowflake architecture and implementation. ARA-C01 exam consists of multiple-choice questions, scenario-based questions, and hands-on exercises that test the candidate's practical skills.

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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.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q35-Q40):

NEW QUESTION # 35
Which security, governance, and data protection features require, at a MINIMUM, the Business Critical edition of Snowflake? (Choose two.)

  • A. AWS, Azure, or Google Cloud private connectivity to Snowflake
  • B. Periodic rekeying of encrypted data
  • C. Extended Time Travel (up to 90 days)
  • D. Federated authentication and SSO
  • E. Customer-managed encryption keys through Tri-Secret Secure

Answer: A,E

Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the security, governance, and data protection features that require, at a minimum, the Business Critical edition of Snowflake are:
* Customer-managed encryption keys through Tri-Secret Secure. This feature allows customers to manage their own encryption keys for data at rest in Snowflake, using a combination of three secrets: a master key, a service key, and a security password. This provides an additional layer of security and control over the data encryption and decryption process1.
* Periodic rekeying of encrypted data. This feature allows customers to periodically rotate the encryption keys for data at rest in Snowflake, using either Snowflake-managed keys or customer-managed keys. This enhances the security and protection of the data by reducing the risk of key compromise or exposure2.
The other options are incorrect because they do not require the Business Critical edition of Snowflake. Option A is incorrect because extended Time Travel (up to 90 days) is available with the Enterprise edition of Snowflake3. Option D is incorrect because AWS, Azure, or Google Cloud private connectivity to Snowflake is available with the Standard edition of Snowflake4. Option E is incorrect because federated authentication and SSO are available with the Standard edition of Snowflake5. References: Tri-Secret Secure | Snowflake Documentation, Periodic Rekeying of Encrypted Data | Snowflake Documentation, Snowflake Editions | Snowflake Documentation, Snowflake Network Policies | Snowflake Documentation, Configuring Federated Authentication and SSO | Snowflake Documentation


NEW QUESTION # 36
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. TEMPORARY
  • B. TRANSIENT
  • C. PERMANENT

Answer: B

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.


NEW QUESTION # 37
A table contains five columns and it has millions of records. The cardinality distribution of the columns is shown below:

Column C4 and C5 are mostly used by SELECT queries in the GROUP BY and ORDER BY clauses.
Whereas columns C1, C2 and C3 are heavily used in filter and join conditions of SELECT queries.
The Architect must design a clustering key for this table to improve the query performance.
Based on Snowflake recommendations, how should the clustering key columns be ordered while defining the multi-column clustering key?

  • A. C5, C4, C2
  • B. C1, C3, C2
  • C. C3, C4, C5
  • D. C2, C1, C3

Answer: B

Explanation:
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


NEW QUESTION # 38
How can an Architect enable optimal clustering to enhance performance for different access paths on a given table?

  • A. Create a clustering key that contains all columns used in the access paths.
  • B. Create multiple clustering keys for a table.
  • C. Create super projections that will automatically create clustering.
  • D. Create multiple materialized views with different cluster keys.

Answer: D

Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the best way to enable optimal clustering to enhance performance for different access paths on a given table is to create multiple materialized views with different cluster keys. A materialized view is a pre-computed result set that is derived from a query on one or more base tables. A materialized view can be clustered by specifying a clustering key, which is a subset of columns or expressions that determines how the data in the materialized view is co-located in micro-partitions. By creating multiple materialized views with different cluster keys, an Architect can optimize the performance of queries that use different access paths on the same base table. For example, if a base table has columns A, B, C, and D, and there are queries that filter on A and B, or on C and D, or on A and C, the Architect can create three materialized views, each with a different cluster key: (A, B), (C, D), and (A, C). This way, each query can leverage the optimal clustering of the corresponding materialized view and achieve faster scan efficiency and better compression.
References:
* Snowflake Documentation: Materialized Views
* Snowflake Learning: Materialized Views
https://www.snowflake.com/blog/using-materialized-views-to-solve-multi-clustering-performance-problems/


NEW QUESTION # 39
A new user user_01 is created within Snowflake. The following two commands are executed:
Command 1-> show grants to user user_01;
Command 2 ~> show grants on user user 01;
What inferences can be made about these commands?

  • A. Command 1 defines which role owns user_01
    Command 2 defines all the grants which have been given to user_01
  • B. Command 1 defines which user owns user_01
    Command 2 defines all the grants which have been given to user_01
  • C. Command 1 defines all the grants which are given to user_01 Command 2 defines which user owns user_01
  • D. Command 1 defines all the grants which are given to user_01 Command 2 defines which role owns user 01

Answer: D

Explanation:
The SHOW GRANTS command in Snowflake can be used to list all the access control privileges that have been explicitly granted to roles, users, and shares. The syntax and the output of the command vary depending on the object type and the grantee type specified in the command1. In this question, the two commands have the following meanings:
Command 1: show grants to user user_01; This command lists all the roles granted to the user user_01. The output includes the role name, the grantee name, and the granted by role name for each grant. This command is equivalent to show grants to user current_user if user_01 is the current user1.
Command 2: show grants on user user_01; This command lists all the privileges that have been granted on the user object user_01. The output includes the privilege name, the grantee name, and the granted by role name for each grant. This command shows which role owns the user object user_01, as the owner role has the privilege to modify or drop the user object2.
Therefore, the correct inference is that command 1 defines all the grants which are given to user_01, and command 2 defines which role owns user_01.
Reference:
SHOW GRANTS
Understanding Access Control in Snowflake


NEW QUESTION # 40
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