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[Hardware] Online ARA-C01 Version | Reliable ARA-C01 Dumps

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【Hardware】 Online ARA-C01 Version | Reliable ARA-C01 Dumps

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P.S. Free 2026 Snowflake ARA-C01 dumps are available on Google Drive shared by TestsDumps: https://drive.google.com/open?id=1OpaYJ2X-7I5qF2RGypZjikXPoTyzuF2w
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To take the Snowflake ARA-C01 Exam, candidates must have previously passed the SnowPro Core Certification and have significant experience working with Snowflake's cloud data warehouse platform. ARA-C01 exam consists of 60 multiple-choice questions and must be completed within 90 minutes. A passing score of 80% or higher is required to earn the SnowPro Advanced Architect Certification, which is recognized by organizations worldwide as a validation of advanced skill and knowledge in Snowflake data warehousing.
By earning the SnowPro Advanced Architect Certification, professionals can demonstrate their expertise in Snowflake's advanced architecture and design principles, which can help them advance their careers and increase their earning potential. SnowPro Advanced Architect Certification certification program is recognized by top employers in the industry, and is a valuable asset for professionals who want to differentiate themselves in the competitive job market. Whether you are a data architect, data engineer, data analyst, or data scientist, the SnowPro Advanced Architect Certification can help you take your career to the next level.
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Snowflake ARA-C01 Certification Exam has a reputation for being one of the most challenging Snowflake certification exams. It requires a deep understanding of Snowflake architecture and features, as well as a strong ability to apply that knowledge to complex real-world scenarios. However, earning this certification can be a significant boost to a professional's career, as it demonstrates their expertise in architecting Snowflake solutions at an advanced level.
Snowflake SnowPro Advanced Architect Certification Sample Questions (Q144-Q149):NEW QUESTION # 144
How do you refresh a materialized view?
  • A. REFRESH MATERIALIZED VIEW <MV_NAME>
  • B. ALTER VIEW <MV_NAME> REFRESH
  • C. Materialized views are automatically refreshed by snowflake and does not require manual intervention
Answer: C

NEW QUESTION # 145
An Architect is designing a solution that will be used to process changed records in an orders table.
Newly-inserted orders must be loaded into the f_orders fact table, which will aggregate all the orders by multiple dimensions (time, region, channel, etc.). Existing orders can be updated by the sales department within 30 days after the order creation. In case of an order update, the solution must perform two actions:
1. Update the order in the f_0RDERS fact table.
2. Load the changed order data into the special table ORDER _REPAIRS.
This table is used by the Accounting department once a month. If the order has been changed, the Accounting team needs to know the latest details and perform the necessary actions based on the data in the order_repairs table.
What data processing logic design will be the MOST performant?
  • A. Usetwo streams and two tasks.
  • B. Useone stream and one task.
  • C. Useone stream and two tasks.
  • D. Usetwo streams and one task.
Answer: C
Explanation:
The most performant design for processing changed records, considering the need to both update records in the f_orders fact table and load changes into the order_repairs table, is to use one stream and two tasks. The stream will monitor changes in the orders table, capturing both inserts and updates. The first task would apply these changes to the f_orders fact table, ensuring all dimensions are accurately represented. The second task would use the same stream to insert relevant changes into the order_repairs table, which is critical for the Accounting department's monthly review. This method ensures efficient processing by minimizing the overhead of managing multiple streams and synchronizing between them, while also allowing specific tasks to optimize for their target operations.References: Snowflake's documentation on streams and tasks for handling data changes efficiently.

NEW QUESTION # 146
Which of the below commands lists all the pipes for which you have access?
  • A. SHOW PIPES()
  • B. LIST PIPES()
  • C. LIST @PIPES
  • D. Display Pipes()
Answer: A

NEW QUESTION # 147
select metadata$filename, metadata$file_row_number from @filestage/data1.json.gz;
Please select the correct statements for the above-mentioned query.
  • A. FILESTAGE is the file name, METADATA$FILE_ROW_NUMBER will give the path to the data file in the stage
  • B. FILESTAGE is the stage name, METADATA$FILE_ROW_NUMBER will give the path to the data file in the stage
  • C. FILESTAGE is the stage name, METADATA$FILE_ROW_NUMBER will give the row number for each record in the container staged data file
Answer: C

NEW QUESTION # 148
You have created a table as below
CREATE TABLE SNOWFLAKE (FLAKE_ID INTEGER, UDEMY_COURSE VARCHAR);
Which of the below select query will fail for this table?
  • A. SELECT * from snowflake;
  • B. SELECT * from "snowflake";
  • C. SELECT * from Snowflake;
  • D. SELECT * FROM "SNOWFLAKE";
Answer: B

NEW QUESTION # 149
......
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