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SOL-C01 Latest Test Sample - Valid SOL-C01 Real Test

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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q172-Q177):

NEW QUESTION # 172
A data engineer is using Snowflake Notebooks to perform a series of transformations on a large dataset. After executing a cell containing a complex SQL query that includes user-defined functions (UDFs), the cell's execution status remains 'Running' for an unexpectedly long time.
What are the MOST likely reasons for this prolonged execution time?

A. The Snowflake Notebook session has timed out due to inactivity.
B. The data being processed is heavily skewed, leading to uneven workload distribution across nodes.
C. The cell is waiting for a lock on a table or object that is currently being modified by another process.
D. The Snowflake warehouse is under-provisioned for the size and complexity of the query.
E. The UDFs within the query are inefficient and causing performance bottlenecks.

Answer: B,C,D,E

Explanation:
Prolonged execution times can be attributed to several factors. Inefficient UDFs (A) directly impact performance. Under-provisioned warehouses (B) lack the resources to execute the query efficiently. Data skew (C) can cause some nodes to work harder than others. Lock contention (E) will cause the cell to wait. Session timeout (D) would result in an error, not a 'Running' status.

NEW QUESTION # 173
What is the PRIMARY purpose for using the PARSE_DOCUMENT function when using a Cortex LLM?

A. To summarize the key points in a document into concise text
B. To translate the content of a document from one language to another
C. To extract content from a document
D. To analyze the sentiment of the content in a document

Answer: C

NEW QUESTION # 174
You have a Snowflake database named 'SALES DB' containing schemas 'RAW' and
'TRANSFORMED'. The 'RAW' schema holds raw data ingested from various sources, and the
'TRANSFORMED' schema contains cleansed and transformed data ready for reporting. You need to grant the 'DATA ANALYST' role the ability to read all tables in the 'TRANSFORMED' schema but prevent them from modifying any objects. What is the MOST efficient and secure way to achieve this?

A. GRANT SELECT ON SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;
B. GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST; GRANT SELECT ON FUTURE TABLES IN SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;
C. GRANT ALL PRIVILEGES ON SCHEMA SALES DB.TRANSFORMED TO ROLE DATA
ANALYST;
D. GRANT SELECT ON ALL TABLES IN SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;
E. GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST; GRANT USAGE ON SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST; GRANT SELECT ON FUTURE TABLES IN SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;

Answer: E

Explanation:
The most efficient and secure approach is to grant USAGE on the DATABASE and SCHEMA, and SELECT on FUTURE TABLES (C). USAGE privilege on the database allows the role to access objects within the database. USAGE on the schema allows access to the schema.
Granting SELECT on FUTURE TABLES ensures that any new tables created in the TRANSFORMED schema will automatically inherit the SELECT privilege for the DATA ANALYST role. Option A only grants SELECT on existing tables, not future ones. Option D grants ALL PRIVILEGES, which is too permissive. Option E is insufficient as it doesn't grant required privileges on Database and Schema. Option B is partially correct but misses granting usage on SCHEMA.

NEW QUESTION # 175
You have a table 'DOCUMENT STORE' with a column 'FILE CONTENT' of type BINARY containing PDF files. You want to extract text from these PDFs using 'PARSE DOCUMENT and store the extracted text along with the file name in a new table 'EXTRACTED TEXT. Which of the following code snippets correctly implements this, assuming you have a virtual warehouse named
'COMPUTE WH'?

Answer: D

Explanation:
Option B is correct because PARSE_DOCUMENT expects a VARCHAR as input, representing the file content. The TO_VARCHAR function converts the BINARY data to a VARCHAR. Option A will cause an error because PARSE DOCUMENT cannot directly process BINARY data. Option C's additional 'PDF' parameter is not the correct syntax. PARSE_DOCUMENT infers file type based on content, unless provided through URL of stage. TO_BINARY is not required here as already stored as binary. OBJECT CONSTRUCT is not the right way, here, but still will expect VARCHAR file content.

NEW QUESTION # 176
A company stores unstructured text data (PDFs, DOCX) in an external stage (AWS S3). They want to use Snowflake Cortex's PARSE DOCUMENT function to extract specific information, but are encountering performance issues and high costs. Which of the following strategies could optimize performance and reduce costs when using PARSE DOCUMENT in this scenario?

A. Utilize Snowflake's caching mechanism by storing parsed results in a separate table and refreshing it periodically, avoiding redundant parsing of the same documents and reduce MAX FILE SIZE to lower value like 'MAX FILE SIZE-8388608'.
B. Reduce the number of documents being processed in a single batch to minimize memory consumption.
C. Increase the size of the virtual warehouse used for processing, even if it means paying for larger compute resources, and use 'MAX in the file format configuration.
D. Pre-process the documents to remove irrelevant sections (e.g., boilerplate text, headers, footers) before loading them into Snowflake for parsing. Also, ensure appropriate partitioning of data in the external stage.
E. Implement a robust error handling mechanism to prevent processing from halting due to malformed or corrupted documents and monitor the Snowflake resource consumption using Snowflake's monitoring tools.

Answer: A,D,E

Explanation:
Option B is correct because pre-processing reduces the amount of data that PARSE_DOCUMENT needs to process. Partitioning in the external stage enables Snowflake to more efficiently retrieve the relevant data. Option C is correct because caching prevents redundant processing and reduce MAX FILE_SIZE to lower value. Option E is correct because error handling ensures processing continues and monitoring provides insights into resource usage. Option A increasing warehouse size and MAX FILE SIZE without other optimizations is often a brute-force approach that doesn't address the root cause of performance problems and leads to unnecessary costs. Option D, limiting batch size, can help with memory issues but doesn't fundamentally improve the efficiency of document parsing.

NEW QUESTION # 177
......

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