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Earning the Snowflake ARA-C01 Certification demonstrates your proficiency in designing and implementing complex data solutions using Snowflake's cloud data platform. It is a testament to your expertise in data warehousing, data integration, and data analytics. SnowPro Advanced Architect Certification certification is recognized globally and provides a competitive advantage in the job market. It also helps you stand out as a leader in the field of data engineering, data architecture, and data management.

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.

Snowflake ARA-C01 or SnowPro Advanced Architect Certification Exam is a challenging and comprehensive test designed to evaluate the skills and knowledge of experienced architects in the use and implementation of Snowflake's cloud-based data warehousing solutions. ARA-C01 exam covers a wide range of topics, including data modeling, designing and optimizing data warehouses, security, performance tuning, and advanced analytics. Passing ARA-C01 exam is a significant achievement that demonstrates a high level of expertise in Snowflake architecture and design.

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q68-Q73):

NEW QUESTION # 68
A user can change object parameters using which of the following roles?

  • A. ACCOUNTADMIN, SECURITYADMIN
  • B. SYSADMIN, SECURITYADMIN
  • C. SECURITYADMIN, USER with PRIVILEGE
  • D. ACCOUNTADMIN, USER with PRIVILEGE

Answer: D

Explanation:
According to the Snowflake documentation, object parameters are parameters that can be set on individual objects such as databases, schemas, tables, and stages. Object parameters can be set by users with the appropriate privileges on the objects. For example, to set the object parameter AUTO_REFRESH on a table, the user must have the MODIFY privilege on the table. The ACCOUNTADMIN role has the highest level of privileges on all objects in the account, so it can set any object parameter on any object. However, other roles, such as SECURITYADMIN or SYSADMIN, do not have the same level of privileges on all objects, so they cannot set object parameters on objects they do not own or have the required privileges on.
Therefore, the correct answer is C. ACCOUNTADMIN, USER with PRIVILEGE.
Reference:
Parameters | Snowflake Documentation
Object Parameters | Snowflake Documentation
Object Privileges | Snowflake Documentation


NEW QUESTION # 69
An Architect is designing a pipeline to stream event data into Snowflake using the Snowflake Kafka connector. The Architect's highest priority is to configure the connector to stream data in the MOST cost-effective manner.
Which of the following is recommended for optimizing the cost associated with the Snowflake Kafka connector?

  • A. Utilize a lower Buffer.count.records in the connector configuration.
  • B. Utilize a higher Buffer.size.bytes in the connector configuration.
  • C. Utilize a lower Buffer.size.bytes in the connector configuration.
  • D. Utilize a higher Buffer.flush.time in the connector configuration.

Answer: D

Explanation:
The minimum value supported for the buffer.flush.time property is 1 (in seconds). For higher average data flow rates, we suggest that you decrease the default value for improved latency. If cost is a greater concern than latency, you could increase the buffer flush time. Be careful to flush the Kafka memory buffer before it becomes full to avoid out of memory exceptions. https://docs.snowflake.com/en/user-guide/data-load-snowpipe-streaming-kafka


NEW QUESTION # 70
The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1) Finance and Vendor Management team members who require reporting and visualization
2) Data Science team members who require access to raw data for ML model development
3) Sales team members who require engineered and protected data for data monetization What Snowflake data modeling approaches will meet these requirements? (Choose two.)

  • A. Consolidate data in the company's data lake and use EXTERNAL TABLES.
  • B. Create a raw database for landing and persisting raw data entering the data pipelines.
  • C. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.
  • D. Create a set of profile-specific databases that aligns data with usage patterns.
  • E. Create a single star schema in a single database to support all consumers' requirements.

Answer: B,D

Explanation:
Explanation
These two approaches are recommended by Snowflake for data modeling in a data lake scenario. Creating a raw database allows the data engineering team to ingest data from various sources without any transformation or cleansing, preserving the original data quality and format. This enables the data science team to access the raw data for ML model development. Creating a set of profile-specific databases allows the data engineering team to apply different transformations and optimizations for different use cases and data consumer requirements. For example, the finance and vendor management team can access a dimensional database that supports reporting and visualization, while the sales team can access a secure database that supports data monetization.
References:
* Snowflake Data Lake Architecture | Snowflake Documentation
* Snowflake Data Lake Best Practices | Snowflake Documentation


NEW QUESTION # 71
Two queries are run on the customer_address table:
create or replace TABLE CUSTOMER_ADDRESS ( CA_ADDRESS_SK NUMBER(38,0), CA_ADDRESS_ID VARCHAR(16), CA_STREET_NUMBER VARCHAR(IO) CA_STREET_NAME VARCHAR(60), CA_STREET_TYPE VARCHAR(15), CA_SUITE_NUMBER VARCHAR(10), CA_CITY VARCHAR(60), CA_COUNTY VARCHAR(30), CA_STATE VARCHAR(2), CA_ZIP VARCHAR(10), CA_COUNTRY VARCHAR(20), CA_GMT_OFFSET NUMBER(5,2), CA_LOCATION_TYPE VARCHAR(20) ); ALTER TABLE DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS ADD SEARCH OPTIMIZATION ON SUBSTRING(CA_ADDRESS_ID); Which queries will benefit from the use of the search optimization service? (Select TWO).

  • A. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where substring(CA_ADDRESS_ID,1,8)= substring('AAAAAAAAPHPPLBAAASKDJHASLKDJHASKJD',1,8);
  • B. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where CA_ADDRESS_ID= substring('AAAAAAAAPHPPLBAAASKDJHASLKDJHASKJD',1,16);
  • C. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where CA_ADDRESS_ID LIKE '%BAAASKD%';
  • D. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where CA_ADDRESS_ID NOT LIKE '%AAAAAAAAPHPPL%';
  • E. select * from DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS Where CA_ADDRESS_ID LIKE '%PHPP%';

Answer: A,B

Explanation:
The use of the search optimization service in Snowflake is particularly effective when queries involve operations that match exact substrings or start from the beginning of a string. The ALTER TABLE command adding search optimization specifically for substrings on the CA_ADDRESS_ID field allows the service to create an optimized search path for queries using substring matches.
Option A benefits because it directly matches a substring from the start of the CA_ADDRESS_ID, aligning with the optimization's capability to quickly locate records based on the beginning segments of strings.
Option B also benefits, despite performing a full equality check, because it essentially compares the full length of CA_ADDRESS_ID to a substring, which can leverage the substring index for efficient retrieval.
Options C, D, and E involve patterns that do not start from the beginning of the string or use negations, which are not optimized by the search optimization service configured for starting substring matches.
Reference: Snowflake's documentation on the use of search optimization for substring matching in SQL queries.


NEW QUESTION # 72
Secure views cannot take advantage of the internal optimizations which require access to the underlying data in the base tables for the view.

  • A. FALSE
  • B. TRUE

Answer: B


NEW QUESTION # 73
......

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