SnowPro Advanced Data Engineer Table Practice 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?

• AA. Create a stream on the staging table and schedule a task that transforms data from the stream only when the stream has data.
• BB. 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 JOIN's.
• CC. 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.
• DD. 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.

A CSV file around 1 TB in size is generated daily on an on-premise server. A corresponding table, internal stage, and file format have already been created in Snowflake to facilitate the data loading process. How can the process of bringing the CSV file into Snowflake be automated using the LEAST amount of operational overhead?

• AA. Create a task in Snowflake that executes once a day and runs a copy into statement that references the internal stage. The internal stage will read the files directly from the on-premise server and copy the newest file into the table from the on-premise server to the Snowflake table
• BB. On the on-premise server schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage. Create a task that executes once a day in Snowflake and runs a COPY INTO statement that references the internal stage. Schedule the task to start after the file lands in the internal stage
• CC. On the on-premise server schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage. Create a pipe that runs a copy into statement that references the internal stage. Snowpipe auto-ingest will automatically load the file from the internal stage when the new file lands in the internal stage.
• DD. On the on-premise server schedule a Python file that uses the Snowpark Python library. The Python script will read the CSV data into a DataFrame and generate an insert into statement that will directly load into the table. The script will bypass the need to move a file into an internal stage

A Data Engineer is trying to load the following rows from a CSV file into a table in Snowflake with the following structure: ....engineer is using the following COPY INTO statement: However, the following error is received. Which file format option should be used to resolve the error and successfully load all the data into the table?

• AA. ESC&PE_UNENGLO9ED_FIELD = '\\'
• BB. ERROR_ON_COLUMN_COUKT_MISMATCH = FALSE
• CC. FIELD_DELIMITER = ","
• DD. FIELD OPTIONALLY ENCLOSED BY = " "