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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q113-Q118):

NEW QUESTION # 113
You are using the 'COPY INTO' command to load data from an Amazon S3 bucket into a Snowflake table named 'employees'. The data in S3 is in CSV format, compressed with gzip, and contains a header row. You want to skip the header row during the load and handle any data conversion errors by continuing the load operation. Which of the following 'COPY INTO' commands is most appropriate?

A. Option C
B. Option A
C. Option E
D. Option B
E. Option D

Answer: B

Explanation:
Option A is the most appropriate. It correctly specifies the S3 bucket and file, CSV file format, skips the header row CSKIP_HEADER = and handles data conversion errors by continuing the load CON_ERROR = 'CONTINUE"). While other options might partially address the requirements, option A is complete and adheres to correct syntax. Option B uses 'SKIP_FILE' which would skip the whole file on error. Option C is closer, but adding `ERROR = FALSE is not directly related to handling data conversion errors. option D is incorrect because 'ON_ERROR = CONTINUE is not a valid syntax, it requires to be in single quotes 'ON ERROR = 'CONTINUE".
Option E is also good but 'FIELD DELIMITER = is not required here and is not adding value.

NEW QUESTION # 114
You are tasked with loading data from a series of CSV files stored in an Amazon S3 bucket into Snowflake. The CSV files contain a header row, but some files have slight variations in the number and order of columns. You want to ensure that all relevant data is loaded correctly, even if the column order differs, and that any extra columns are ignored. Which of the following approaches is the MOST appropriate and efficient?

A. Define a single external table with a VARIANT column and use Snowflake's CSV parsing capabilities to load all files into that column. Then, extract the relevant data using JSON path expressions.
B. Pre-process the CSV files to standardize the column order and names before loading them into Snowflake.
C. Create a separate external table for each CSV file with a different column structure.
D. Create a VIEW on top of the external table to ensure that column names are consistent across all files.
Then load the data into view.
E. Create a single target table with all possible columns from all CSV files, using 'SKIP_HEADER = 1' and explicitly map the columns in the 'COPY INTO' statement to the correct columns in the target table, using the 'FILE FORMAT option to specify the correct field delimiter.

Answer: E

Explanation:
Creating a single target table with all possible columns and explicitly mapping the columns in the
'COPY INTO' statement is the most appropriate. This approach handles variations in column order by explicitly mapping columns from the CSV files to the target table. It is more performant than VARIANT, and doesn't require external preprocessing. Option A is not scalable and difficult to maintain. Option B is suitable for schema evolution but is not recommended if schemas are already known. Option D loading data into view, is not direct approach, and requires external table and COPY command need a table not view to load. Option E pre-processing helps if data consistency is high priority, but adds complexity to workflow and is not part of Snowflake functionalities.

NEW QUESTION # 115
You are loading data from an external stage into a Snowflake table. Some of the rows in the data files contain invalid characters that cause the load operation to fail. You want to configure the
'COPY INTO' command to skip these rows while continuing to load valid data. Which of the following options is the MOST efficient way to handle these errors during the data loading process?

A. Option D
B. Option C
C. Option A
D. Option E
E. Option B

Answer: A

NEW QUESTION # 116
You are working with a Snowflake Notebook to process data from an external stage (AWS S3).
You need to access the S3 stage using a named stage object and a storage integration configured with IAM roles. Which of the following options represents the correct sequence of steps and Snowflake SQL commands within the notebook to achieve this?

A. 1. Create the external stage specifying the S3 bucket URL and credentials. 2. Create a file format object. 3. Use 'SELECT FROM @stage/file.csv' to query the data directly from the stage.
B. 1. Create the storage integration with appropriate IAM roles. 2. Use the 'LIST @stage' command to verify the stage connectivity and file listing. 3. Create an external table pointing to the external stage. 4. Use the 'REFRESH EXTERNAL TABLE command to load the metadata. 5. Query data directly from the external table.
C. 1. Create the storage integration with appropriate IAM roles. 2. Create the external stage referencing the storage integration. 3. Use 'COPY INTO' command to load data from the stage into a Snowflake table, specifying the stage name.
D. 1. Create the external stage specifying the S3 bucket URL and credentials. 2. Create a file format object. 3. Use `COPY INTO' command to load data from the stage into a Snowflake table, specifying the stage name and the file format.
E. 1. Create the storage integration with appropriate IAM roles. 2. Create the external stage referencing the storage integration. 3. Create a file format object. 4. Use `COPY INTO command to load data from the stage into a Snowflake table, specifying the stage name and the file format.

Answer: C,E

Explanation:
Options A and D are correct. The correct and secure approach involves using storage integrations with IAM roles. Creating the storage integration first establishes trust between Snowflake and AWS. The stage then references this integration. The 'COPY INTO' command (Option A) is used for loading data into Snowflake tables. External tables (option C) are read-only and designed for querying data in place, not loading it. Option D Corrects A by including the file format, which is generally required. Option B does not use storage integrations, which is more secure . Option E Requires credential in stage definition, which is not encouraged.

NEW QUESTION # 117
A data engineer is tasked with creating a new database called `SALES DATA within a Snowflake account. They want to ensure that only users with the 'ACCOUNTADMIN' role or a custom role
'SALES ADMIN' can manage the database's overall configuration. Which of the following steps are necessary to achieve this? (Choose all that apply)

A. Grant the `MODIFY privilege on the DATABASE object to the 'SALES_ADMIN' role.
B. Grant the `OWNERSHIP' privilege on the 'SALES_DATX database to the 'SALES_ADMIN' role.
C. The 'ACCOUNTADMIN' role already has sufficient privileges; no additional grants are needed for it.
D. Grant the `CREATE SCHEMA' privilege on the `SALES DATA' database to the 'SALES_ADMIN' role.
E. Grant the `USAGE privilege on the 'DATABASE object to the `SALES ADMINS role.

Answer: B,C

Explanation:
The 'OWNERSHIP' privilege grants the 'SALES ADMIN' role full control over the 'SALES DATA' database, including configuration. ACCOUNTADMIN' inherently has ownership over all objects and requires no additional grants. 'CREATE SCHEMA' is for creating schemas within the database, 'MODIFY is not a valid privilege on 'DATABASE object, and ` USAGE allows access but not management of the database object itself.

NEW QUESTION # 118
......

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