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Free PDF Quiz Marvelous Snowflake - ARA-C01 - Exams SnowPro Advanced Architect Certification Torrent

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Snowflake ARA-C01 (SnowPro Advanced Architect Certification) is a professional certification exam designed to validate the skills and knowledge of data architects and engineers who specialize in designing and implementing complex Snowflake cloud data platforms. SnowPro Advanced Architect Certification certification exam is recognized globally by companies that use Snowflake for their data management, warehousing, and analytics needs.

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To be eligible to take the SnowPro Advanced Architect Certification exam, candidates must have a solid understanding of Snowflake data warehousing and data management concepts, as well as practical experience in designing and implementing Snowflake solutions. Candidates are also required to have completed the SnowPro Core Certification exam, which tests their foundational knowledge of Snowflake data warehousing and data management.

Snowflake ARA-C01 Exam is one of the most sought-after certifications in the data analytics industry. It provides professionals with the opportunity to demonstrate their expertise in Snowflake's advanced concepts and techniques. SnowPro Advanced Architect Certification certification program is designed to validate the candidate's knowledge of data warehousing, data modeling, ETL, security, and performance optimization best practices in a Snowflake environment.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q24-Q29):

NEW QUESTION # 24
A company has a Snowflake account named ACCOUNTA in AWS us-east-1 region. The company stores its marketing data in a Snowflake database named MARKET_DB. One of the company's business partners has an account named PARTNERB in Azure East US 2 region. For marketing purposes the company has agreed to share the database MARKET_DB with the partner account.
Which of the following steps MUST be performed for the account PARTNERB to consume data from the MARKET_DB database?

A. From account ACCOUNTA create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then make this database the provider and share it with the PARTNERB account.
B. Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA create a share of database MARKET_DB, create a new database out of this share locally in AWS us-east-1 region, and replicate this new database to AZABC123 account. Then set up data sharing to the PARTNERB account.
C. Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA replicate the database MARKET_DB to AZABC123 and from this account set up the data sharing to the PARTNERB account.
D. Create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then replicate this database to the partner's account PARTNERB.

Answer: C

Explanation:
* Snowflake supports data sharing across regions and cloud platforms using account replication and share replication features. Account replication enables the replication of objects from a source account to one or more target accounts in the same organization. Share replication enables the replication of shares from a source account to one or more target accounts in the same organization1.
* To share data from the MARKET_DB database in the ACCOUNTA account in AWS us-east-1 region with the PARTNERB account in Azure East US 2 region, the following steps must be performed:
* Create a new account (called AZABC123) in Azure East US 2 region. This account will act as a bridge between the source and the target accounts. The new account must be linked to the ACCOUNTA account using an organization2.
* From the ACCOUNTA account, replicate the MARKET_DB database to the AZABC123 account using the account replication feature. This will create a secondary database in the AZABC123 account that is a replica of the primary database in the ACCOUNTA account3.
* From the AZABC123 account, set up the data sharing to the PARTNERB account using the share replication feature. This will create a share of the secondary database in the AZABC123 account and grant access to the PARTNERB account. The PARTNERB account can then create a database from the share and query the data4.
* Therefore, option C is the correct answer.
References: : Replicating Shares Across Regions and Cloud Platforms : Working with Organizations and Accounts : Replicating Databases Across Multiple Accounts : Replicating Shares Across Multiple Accounts

NEW QUESTION # 25
Role A has the following permissions:
. USAGE on db1
. USAGE and CREATE VIEW on schemal in db1
. SELECT on tablel in schemal
Role B has the following permissions:
. USAGE on db2
. USAGE and CREATE VIEW on schema2 in db2
. SELECT on table2 in schema2
A user has Role A set as the primary role and Role B as a secondary role.
What command will fail for this user?

A. use database db2;
use schema schema2;
select * from db1.schemal.tablel union select * from table2;
B. use database db2;
use schema schema2;
create view v2 as select * from dbl.schemal. tablel;
C. use database db1;
use schema schemal;
create view v1 as select * from db2.schema2.table2;
D. use database db1;
use schema schemal;
select * from db2.schema2.table2;

Answer: B

Explanation:
This command will fail because while the user has USAGE permission on db2 and schema2 through Role B, and can create a view in schema2, they do not have SELECT permission on db1.schemal.table1 with Role B. Since Role A, which has SELECT permission on db1.schemal.table1, is not the currently active role when the view v2 is being created in db2.schema2, the user does not have the necessary permissions to read from db1.schemal.table1 to create the view. Snowflake's security model requires that the active role have all necessary permissions to execute the command.

NEW QUESTION # 26
What step will improve the performance of queries executed against an external table?

A. Partition the external table.
B. Convert the source files' character encoding to UTF-8.
C. Use an internal stage instead of an external stage to store the source files.
D. Shorten the names of the source files.

Answer: A

Explanation:
Partitioning an external table is a technique that improves the performance of queries executed against the table by reducing the amount of data scanned. Partitioning an external table involves creating one or more partition columns that define how the table is logically divided into subsets of data based on the values in those columns. The partition columns can be derived from the file metadata (such as file name, path, size, or modification time) or from the file content (such as a column value or a JSON attribute). Partitioning an external table allows the query optimizer to prune the files that do not match the query predicates, thus avoiding unnecessary data scanning and processing2 The other options are not effective steps for improving the performance of queries executed against an external table:
* Shorten the names of the source files. This option does not have any impact on the query performance, as the file names are not used for query processing. The file names are only used for creating the external table and displaying the query results3
* Convert the source files' character encoding to UTF-8. This option does not affect the query performance, as Snowflake supports various character encodings for external table files, such as UTF-8,
* UTF-16, UTF-32, ISO-8859-1, and Windows-1252. Snowflake automatically detects the character encoding of the files and converts them to UTF-8 internally for query processing4
* Use an internal stage instead of an external stage to store the source files. This option is not applicable, as external tables can only reference files stored in external stages, such as Amazon S3, Google Cloud Storage, or Azure Blob Storage. Internal stages are used for loading data into internal tables, not external tables5 References:
* 1: SnowPro Advanced: Architect | Study Guide
* 2: Snowflake Documentation | Partitioning External Tables
* 3: Snowflake Documentation | Creating External Tables
* 4: Snowflake Documentation | Supported File Formats and Compression for Staged Data Files
* 5: Snowflake Documentation | Overview of Stages
* : SnowPro Advanced: Architect | Study Guide
* : Partitioning External Tables
* : Creating External Tables
* : Supported File Formats and Compression for Staged Data Files
* : Overview of Stages

NEW QUESTION # 27
A group of Data Analysts have been granted the role analyst role. They need a Snowflake database where they can create and modify tables, views, and other objects to load with their own data. The Analysts should not have the ability to give other Snowflake users outside of their role access to this data.
How should these requirements be met?

A. Make every schema in the database a managed access schema, owned by SYSADMIN, and grant create privileges on each schema to the ANALYST_ROLE for each type of object that needs to be created.
B. Grant SYSADMIN ownership of the database, but grant the create schema privilege on the database to the ANALYST_ROLE.
C. Grant ANALYST_R0LE OWNERSHIP on the database, but make sure that ANALYST_ROLE does not have the MANAGE GRANTS privilege on the account.
D. Grant ANALYST_ROLE ownership on the database, but grant the ownership on future [object type] s in database privilege to SYSADMIN.

Answer: A

Explanation:
The requirements state that the data analysts need to be able to create and modify database objects and load data, but should not be able to manage access for users outside of their role.
Option C: By making each schema within the database a managed access schema and having them owned by SYSADMIN, the ability to grant privileges on the schema's objects is strictly controlled. Managed access schemas limit the granting of privileges to the role specified as the owner of the schema, in this case, SYSADMIN. The ANALYST_ROLE can be granted the privileges necessary to create and modify objects within these schemas, satisfying the requirement for the analysts to perform their tasks without being able to extend access beyond their role.

NEW QUESTION # 28
What Snowflake system functions are used to view and or monitor the clustering metadata for a table? (Select TWO).

A. SYSTEMSCLUSTERING
B. SYSTEMSCLUSTERING_RATIO
C. SYSTEMSCLUSTERING_DEPTH
D. SYSTEMSCLUSTERING_INFORMATION
E. SYSTEMSTABLE_CLUSTERING

Answer: C,D

Explanation:
The Snowflake system functions used to view and monitor the clustering metadata for a table are:
* SYSTEM$CLUSTERING_INFORMATION
* SYSTEM$CLUSTERING_DEPTH
Comprehensive But Short Explanation:
* The SYSTEM$CLUSTERING_INFORMATION function in Snowflake returns a variety of clustering information for a specified table. This information includes the average clustering depth, total number of micro-partitions, total constant partition count, average overlaps, average depth, and a partition depth histogram. This function allows you to specify either one or multiple columns for which the clustering information is returned, and it returns this data in JSON format.
* The SYSTEM$CLUSTERING_DEPTH function computes the average depth of a table based on specified columns or the clustering key defined for the table. A lower average depth indicates that the table is better clustered with respect to the specified columns. This function also allows specifying columns to calculate the depth, and the values need to be enclosed in single quotes.
References:
* SYSTEM$CLUSTERING_INFORMATION: Snowflake Documentation
* SYSTEM$CLUSTERING_DEPTH: Snowflake Documentation

NEW QUESTION # 29
......

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