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Exam SnowPro Advanced Data Engineer All Questions

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Exam SnowPro Advanced Data Engineer topic 1 question 54 discussion

Actual exam question from Snowflake's SnowPro Advanced Data Engineer
Question #: 54
Topic #: 1
[All SnowPro Advanced Data Engineer Questions]

A company is using Snowpipe to bring in millions of rows every day of Change Data Capture (CDC) into a Snowflake staging table on a real-time basis. The CDC needs to get processed and combined with other data in Snowflake and land in a final table as part of the full data pipeline.
How can a Data Engineer MOST efficiently process the incoming CDC on an ongoing basis?

  • A. Create a stream on the staging table and schedule a task that transforms data from the stream, only when the stream has data.
  • B. Transform the data during the data load with Snowpipe by modifying the related COPY INTO statement to include transformation steps such as CASE statements and JOINS.
  • C. Schedule a task that dynamically retrieves the last time the task was run from information_schema.task_history and use that timestamp to process the delta of the new rows since the last time the task was run.
  • D. Use a CREATE OR REPLACE TABLE AS statement that references the staging table and includes all the transformation SQL. Use a task to run the full CREATE OR REPLACE TABLE AS statement on a scheduled basis.
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Suggested Answer: A 🗳️
by stopthisnow at Nov. 16, 2023, 7:22 p.m.

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stopthisnow
1 month, 1 week ago
Selected Answer: A
A makes sense. D is definitely wrong. Can't drop and create table every time, it will also loose previous data. Needs to be incremental
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