Snowflake GES-C01

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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1.

A)

B)

C)

D)

E)

2. A Gen AI specialist is preparing to upload a large volume of diverse documents to an internal stage for Document AI processing. The objective is to extract detailed information, including lists of items and potentially classifying document types, and then automate this process. Which of the following statements represent 'best practices or important considerations/limitations' when preparing documents and setting up the Document AI workflow in Snowflake? (Select ALL that apply.)

A) To improve model training, documents uploaded should represent a real use case, and the dataset should consist of diverse documents in terms of both layout and data.
B) Documents with a page count exceeding 125 pages or a file size greater than 50 MB will be processed, but with a potential reduction in extraction accuracy.
C) If the Document AI model does not find an answer for a specific field, the '!PREDICT method will omit the 'value' key but will still return a 'score' key to indicate confidence that the answer is not present.
D) When defining data values for extraction, especially for nonstandard formats or combinations of values, fine-tuning the model with annotations is generally more effective than relying solely on complex prompt engineering.
E) For continuous processing of new documents, it is best practice to create a stream on the internal stage and a task to automate the '!PREDICT method execution.

3. A data operations team is attempting to scale up their Document AI automated pipeline. They are using a Snowflake Task to process a large volume of daily scanned invoices and receipts, which are stored in an internal stage 'financial_docs stage'. The current processing involves documents that are frequently around 75 MB each, and often there are batches exceeding 1 ,200 documents in a single day. The pipeline is failing consistently. Which of the following factors could be contributing to the failures in this Document AI automated pipeline? (Select all that apply.)

A) The Snowflake Task is configured as a 'SERVERLESS TASK, which is not supported by Document AI.
B) The individual document size (75 MB) exceeds the maximum supported file size for Document AI.
C) The was created without specifying 'ENCRYPTION = (TYPE = 'SNOWFLAKE SSE')'.
D) The number of documents in a single daily batch (exceeding 1 ,200) surpasses Document AI's processing limit per query.
E) The account role executing the task lacks the 'SNOWFLAKCORTEX USER database role, which is a prerequisite for Document AI functions.

4.

A)

B)

C)

D)

E)

5. A data scientist is designing a real-time similarity search feature in Snowflake using product embeddings. They plan to use VECTOR_L2_DISTANCE to find similar products. Which statement correctly identifies a cost or data type characteristic relevant to this implementation?

A) Storing product embeddings generated by
B) The
C) The maximum dimension supported for a
D) Both the
E) The

Solutions: