QUIZ 2025 UPDATED SNOWFLAKE ARA-C01: EXAM SNOWPRO ADVANCED ARCHITECT CERTIFICATION EXPERIENCE

Quiz 2025 Updated Snowflake ARA-C01: Exam SnowPro Advanced Architect Certification Experience

Quiz 2025 Updated Snowflake ARA-C01: Exam SnowPro Advanced Architect Certification Experience

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Tags: Exam ARA-C01 Experience, ARA-C01 Test Quiz, ARA-C01 Related Certifications, ARA-C01 Reliable Exam Pass4sure, ARA-C01 Exam Preparation

If you want to through the Snowflake ARA-C01 certification exam to make a stronger position in today's competitive IT industry, then you need the strong expertise knowledge and the accumulated efforts. And pass the Snowflake ARA-C01 exam is not easy. Perhaps through Snowflake ARA-C01 exam you can promote yourself to the IT industry. But it is not necessary to spend a lot of time and effort to learn the expertise. You can choose ValidExam's Snowflake ARA-C01 Exam Training materials. This is training product that specifically made for IT exam. With it you can pass the difficult Snowflake ARA-C01 exam effortlessly.

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.

Snowflake ARA-C01 (SnowPro Advanced Architect Certification) certification exam is one of the most sought-after certifications in the field of cloud computing. It is a comprehensive exam that assesses the skills and knowledge of professionals in designing, deploying, and managing complex Snowflake environments. SnowPro Advanced Architect Certification certification validates the expertise of an individual in building and maintaining Snowflake data warehouses, data lakes, and data pipelines.

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Snowflake ARA-C01 certification exam is designed to test a candidate's knowledge and skills related to Snowflake's advanced architectural concepts. It is a rigorous exam that requires candidates to have a strong understanding of Snowflake's architecture, data modeling, performance tuning, security, and data integration. ARA-C01 Exam is divided into multiple sections, each of which covers a specific topic related to Snowflake's architecture. Candidates must demonstrate their proficiency in each section to earn their certification.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q82-Q87):

NEW QUESTION # 82
When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)

  • A. Avro
  • B. JSON
  • C. XML
  • D. Parquet
  • E. CSV

Answer: A,B


NEW QUESTION # 83
A data platform team creates two multi-cluster virtual warehouses with the AUTO_SUSPEND value set to NULL on one. and '0' on the other. What would be the execution behavior of these virtual warehouses?

  • A. Setting a '0' or NULL value means the warehouses will never suspend.
  • B. Setting a '0' or NULL value means the warehouses will suspend after the default of 600 seconds.
  • C. Setting a '0' or NULL value means the warehouses will suspend immediately.
  • D. Setting a '0' value means the warehouses will suspend immediately, and NULL means the warehouses will never suspend.

Answer: D

Explanation:
The AUTO_SUSPEND parameter controls the amount of time, in seconds, of inactivity after which a warehouse is automatically suspended. If the parameter is set to NULL, the warehouse never suspends. If the parameter is set to '0', the warehouse suspends immediately after executing a query. Therefore, the execution behavior of the two virtual warehouses will be different depending on the AUTO_SUSPEND value. The warehouse with NULL value will keep running until it is manually suspended or the resource monitor limits are reached. The warehouse with '0' value will suspend as soon as it finishes a query and release the compute resources. References:
* ALTER WAREHOUSE
* Parameters


NEW QUESTION # 84

Based on the architecture in the image, how can the data from DB1 be copied into TBL2? (Select TWO).

  • A. A white background with black text Description automatically generated
  • B. A white background with black text Description automatically generated
  • C. A computer code with black text Description automatically generated
  • D. A close-up of a computer code Description automatically generated
  • E. A close-up of a computer code Description automatically generated

Answer: B,E

Explanation:
* The architecture in the image shows a Snowflake data platform with two databases, DB1 and DB2, and two schemas, SH1 and SH2. DB1 contains a table TBL1 and a stage STAGE1. DB2 contains a table TBL2. The image also shows a snippet of code written in SQL language that copies data from STAGE1 to TBL2 using a file format FF PIPE 1.
* To copy data from DB1 to TBL2, there are two possible options among the choices given:
* Option B: Use a named external stage that references STAGE1. This option requires creating an external stage object in DB2.SH2 that points to the same location as STAGE1 in DB1.SH1. The external stage can be created using the CREATE STAGE command with the URL parameter specifying the location of STAGE11. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
use database DB2;
use schema SH2;
create stage EXT_STAGE1
url = @DB1.SH1.STAGE1;
* Then, the data can be copied from the external stage to TBL2 using the COPY INTO command with the FROM parameter specifying the external stage name and the FILE FORMAT parameter specifying the file format name2. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
copy into TBL2
from @EXT_STAGE1
file format = (format name = DB1.SH1.FF PIPE 1);
* Option E: Use a cross-database query to select data from TBL1 and insert into TBL2. This option requires using the INSERT INTO command with the SELECT clause to query data from TBL1 in DB1.SH1 and insert it into TBL2 in DB2.SH2. The query must use the fully-qualified names of the tables, including the database and schema names3. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
use database DB2;
use schema SH2;
insert into TBL2
select * from DB1.SH1.TBL1;
* The other options are not valid because:
* Option A: It uses an invalid syntax for the COPY INTO command. The FROM parameter cannot specify a table name, only a stage name or a file location2.
* Option C: It uses an invalid syntax for the COPY INTO command. The FILE FORMAT parameter cannot specify a stage name, only a file format name or options2.
* Option D: It uses an invalid syntax for the CREATE STAGE command. The URL parameter cannot specify a table name, only a file location1.
References:
* 1: CREATE STAGE | Snowflake Documentation
* 2: COPY INTO table | Snowflake Documentation
* 3: Cross-database Queries | Snowflake Documentation


NEW QUESTION # 85
What considerations need to be taken when using database cloning as a tool for data lifecycle management in a development environment? (Select TWO).

  • A. The clone inherits all granted privileges of all child objects in the source object, including the database.
  • B. Any pipes in the source referring to external stages are not cloned.
  • C. The clone inherits all granted privileges of all child objects in the source object, excluding the database.
  • D. Any pipes in the source are not cloned.
  • E. Any pipes in the source referring to internal stages are not cloned.

Answer: A,D

Explanation:
Database cloning is a feature of Snowflake that allows creating a copy of a database, schema, table, or view without consuming any additional storage space. Database cloning can be used as a tool for data lifecycle management in a development environment, where developers and testers can work on isolated copies of production data without affecting the original data or each other1.
However, there are some considerations that need to be taken when using database cloning in a development environment, such as:
* Any pipes in the source are not cloned. Pipes are objects that load data from a stage into a table continuously. Pipes are not cloned because they are associated with a specific stage and table, and cloning them would create duplicate data loading and potential conflicts2.
* The clone inherits all granted privileges of all child objects in the source object, including the database.
Privileges are the permissions that control the access and actions that can be performed on an object.
When a database is cloned, the clone inherits all the privileges that were granted on the source database and its child objects, such as schemas, tables, and views. This means that the same roles that can access and modify the source database can also access and modify the clone, unless the privileges are explicitly revoked or modified3.
The other options are not correct because:
* B. Any pipes in the source referring to internal stages are not cloned. This is a subset of option A, which states that any pipes in the source are not cloned, regardless of the type of stage they refer to.
* C. Any pipes in the source referring to external stages are not cloned. This is also a subset of option A, which states that any pipes in the source are not cloned, regardless of the type of stage they refer to.
* E. The clone inherits all granted privileges of all child objects in the source object, excluding the database. This is incorrect, as the clone inherits all granted privileges of the source object, including the database.
References:
* 1: Database Cloning | Snowflake Documentation
* 2: Pipes | Snowflake Documentation
* 3: Access Control Privileges | Snowflake Documentation


NEW QUESTION # 86
What Snowflake features should be leveraged when modeling using Data Vault?

  • A. Snowflake's support of multi-table inserts into the data model's Data Vault tables
  • B. Scaling up the virtual warehouses will support parallel processing of new source loads
  • C. Snowflake's ability to hash keys so that hash key joins can run faster than integer joins
  • D. Data needs to be pre-partitioned to obtain a superior data access performance

Answer: A,B

Explanation:
These two features are relevant for modeling using Data Vault on Snowflake. Data Vault is a data modeling approach that organizes data into hubs, links, and satellites. Data Vault is designed to enable high scalability, flexibility, and performance for data integration and analytics. Snowflake is a cloud data platform that supports various data modeling techniques, including Data Vault. Snowflake provides some features that can enhance the Data Vault modeling, such as:
Snowflake's support of multi-table inserts into the data model's Data Vault tables. Multi-table inserts (MTI) are a feature that allows inserting data from a single query into multiple tables in a single DML statement. MTI can improve the performance and efficiency of loading data into Data Vault tables, especially for real-time or near-real-time data integration. MTI can also reduce the complexity and maintenance of the loading code, as well as the data duplication and latency12.
Scaling up the virtual warehouses will support parallel processing of new source loads. Virtual warehouses are a feature that allows provisioning compute resources on demand for data processing. Virtual warehouses can be scaled up or down by changing the size of the warehouse, which determines the number of servers in the warehouse. Scaling up the virtual warehouses can improve the performance and concurrency of processing new source loads into Data Vault tables, especially for large or complex data sets. Scaling up the virtual warehouses can also leverage the parallelism and distribution of Snowflake's architecture, which can optimize the data loading and querying34.
Reference:
Snowflake Documentation: Multi-table Inserts
Snowflake Blog: Tips for Optimizing the Data Vault Architecture on Snowflake Snowflake Documentation: Virtual Warehouses Snowflake Blog: Building a Real-Time Data Vault in Snowflake


NEW QUESTION # 87
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ARA-C01 Test Quiz: https://www.validexam.com/ARA-C01-latest-dumps.html

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