Snowflake SOL-C01 - PDF電子當

SOL-C01 pdf
  • 考試編碼:SOL-C01
  • 考試名稱:Snowflake Certified SnowPro Associate - Platform Certification
  • 更新時間:2025-10-10
  • 問題數量:320 題
  • PDF價格: $59.98
  • 電子當(PDF)試用

Snowflake SOL-C01 超值套裝
(通常一起購買,贈送線上版本)

SOL-C01 Online Test Engine

在線測試引擎支持 Windows / Mac / Android / iOS 等, 因爲它是基於Web瀏覽器的軟件。

  • 考試編碼:SOL-C01
  • 考試名稱:Snowflake Certified SnowPro Associate - Platform Certification
  • 更新時間:2025-10-10
  • 問題數量:320 題
  • PDF電子當 + 軟件版 + 在線測試引擎(免費送)
  • 套餐價格: $119.96  $79.98
  • 節省 50%

Snowflake SOL-C01 - 軟件版

SOL-C01 Testing Engine
  • 考試編碼:SOL-C01
  • 考試名稱:Snowflake Certified SnowPro Associate - Platform Certification
  • 更新時間:2025-10-10
  • 問題數量:320 題
  • 軟件版價格: $59.98
  • 軟件版

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最新的 SnowPro Advanced SOL-C01 免費考試真題:

1. A data science team needs to access data from several databases and schemas for model training. To simplify access management, you create a custom role, `DATA SCIENCE ROLE.
You need to grant this role the ability to SELECT from all tables in any schema across the following databases: `DB ANALYTICS, 'DB REPORTING'. Which of the following is the MOST efficient approach, minimizing the number of GRANT statements while adhering to least privilege?

A) Option E
B) Option B
C) Option C
D) Option A
E) Option D


2. A data scientist is working on a machine learning project using Snowflake Notebooks. They have a dataset stored in Snowflake and need to perform feature engineering. They want to write a Python function that takes a Snowflake table name and a list of SQL expressions as input, executes these expressions against the table, and returns a Pandas DataFrame containing the new features. Which approach is MOST suitable for creating and executing this function within a Snowflake Notebook, minimizing data transfer outside of Snowflake?

A) Use the `snowflake.connectors library to connect to Snowflake, execute each SQL expression using the method, and append the results to a Pandas DataFrame.
B) Use the Snowflake web UI to create a view containing the feature engineered data. Load that view into the notebook as a Pandas DataFrame.
C) Create a Snowflake User-Defined Function (UDF) that encapsulates the feature engineering logic, and then call this UDF from the notebook using Snowpark or standard SQL.
D) Use the `snowflake.snowpark.functions.call_udf to call a UDF from Snowflake notebooks and create a dataframe.
E) Utilize the `sqlalchemy' library to establish a connection to Snowflake, construct the SQL query dynamically using SQLAlchemy's expression language, and fetch the results into a Pandas DataFrame.


3. A data engineer is tasked with using Snowflake Cortex's COMPLETE function to generate concise summaries of customer reviews stored in a table named `CUSTOMER REVIEWS. The
'CUSTOMER REVIEWS' table contains a column named 'REVIEW TEXT' with the raw review text. They want to optimize for cost and performance. Which of the following SQL snippets represents the MOST efficient and cost-effective way to achieve this, assuming the summaries should ideally be no more than 50 words?

A) Option E
B) Option B
C) Option C
D) Option A
E) Option D


4. A company utilizes Snowflake's elastic compute capabilities for its daily batch processing jobs.
They have noticed that the warehouse consistently scales up to X-Large during the peak processing window (8 PM to 10 PM PST) and then scales back down. However, the cost of running the X-Large warehouse for these 2 hours is becoming significant. They are considering optimizing their compute costs. Which of the following strategies would be the MOST effective in reducing compute costs without significantly impacting the overall processing time of the batch jobs?

A) Switch to using Snowflake's Serverless tasks for the batch processing jobs. Serverless tasks automatically manage compute resources and optimize costs based on actual usage.
B) Analyze the SQL queries executed during the batch jobs and identify inefficient queries that consume excessive compute resources. Optimize these queries by rewriting them, adding appropriate indexes, or leveraging Snowflake's query optimization features.
C) Reduce the warehouse size to Large to decrease the hourly compute cost. While this will reduce costs, it will likely increase the overall processing time.
D) Implement workload management rules to prioritize critical queries during the peak processing window. This can improve the efficiency of the warehouse and potentially reduce the need for scaling up to X-Large.
E) Enable auto-suspend for the warehouse with a shorter timeout period (e.g., 5 minutes). This will ensure the warehouse suspends quickly when idle, minimizing unnecessary compute usage.


5. You need to create a database named 'SALES DB' that is only accessible to users with the
'ACCOUNTADMIN' role. After the database is created, you want to grant the 'USAGE' privilege on it to a custom role named 'DATA ANALYST. Which sequence of commands is the MOST efficient and correct way to achieve this?

A) USE ROLE ACCOUNTADMIN; CREATE DATABASE SALES DB; GRANT USAGE ON
DATABASE SALES DB TO ROLE DATA ANALYST;
B) CREATE OR REPLACE DATABASE SALES DB; GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST;
C) USE ROLE ACCOUNTADMIN; CREATE OR REPLACE DATABASE SALES DB; GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST,
D) USE ROLE ACCOUNTADMIN; CREATE DATABASE SALES DB; GRANT USAGE ON
DATABASE SALES DB TO ROLE DATA ANALYST; USE ROLE DATA ANALYST;
E) CREATE DATABASE SALES DB; GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST;


問題與答案:

問題 #1
答案: C
問題 #2
答案: C
問題 #3
答案: E
問題 #4
答案: A,B
問題 #5
答案: C

9位客戶反饋客戶反饋 (* 一些類似或舊的評論已被隱藏。)

59.126.85.* - 

我成功的通過了第一次參加的SOL-C01考試,你們的學習資料真的很不錯,和真實考試中的問題有95%的相似性。

59.120.148.* - 

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114.35.47.* - 

Sfyc-Ru 考古題讓我通過了 SOL-C01 考試,大多數實際考試中的問題都來自這里的考古題。請注意,你們必須小心地通過每一個問題,因為在測試中沒有返回按鈕。

175.182.142.* - 

我的SOL-C01考試通過了,你們的考試培訓資料确实在考試中帮了我很多,謝謝!

117.136.54.* - 

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173.88.197.* - 

這考古題很好,我通過了第一次嘗試參加的SOL-C01認證考試,它涵蓋了我需要知道的考試題庫,幫助我輕松通過!

122.147.141.* - 

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你們提供的考題非常容易理解,對我的Snowflake的SOL-C01考試來說,這是非常優秀的學習指南資料,在我的認證考試中起了很大的幫助。

114.25.19.* - 

很好,是的,很好,90%的真實考試的問題可以在這個考古題中找到!

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