Free Snowflake ARA-C01 Exam Questions

Become Snowflake Certified with updated ARA-C01 exam questions and correct answers

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Total 449 Questions | Updated On: Dec 18, 2025

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Question 1

You have create a task as below

CREATE TASK mytask1

WAREHOUSE = mywh

SCHEDULE = '5 minute'

WHEN

SYSTEM$STREAM_HAS_DATA('MYSTREAM')

INSERT INTO mytable1(id,name) SELECT id, name FROM mystream WHERE METADATA$ACTION = 'INSERT';

Which statement is true below?

A : If SYSTEM$STREAM_HAS_DATA returns false, the task will be skipped

B : If SYSTEM$STREAM_HAS_DATA returns false, the task will still run

C : If SYSTEM$STREAM_HAS_DATA returns false, the task will go to suspended mode

Answer: A

Question 2

Which of these Snowflake components/objects is NOT typically used in building continuous ELT pipelines?

A : Data Exchange

B : Snowflake Connector for Kafka

C : Streams

D : Snowpipe

Answer: A

Question 3

A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables. The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database. What step can be taken to improve the pruning of the reporting tables?

A : Eliminate the use of Snowpipe and load the files into internal stages using PUT commands.

B : Increase the size of the virtual warehouse to a size 5X-Large.

C : Use an ORDER BY command to load the reporting tables.

D : Create larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.

Answer: C

Question 4

Data replication in snowflake helps in

A : Disaster recovery

B : Data sharing

C : Account Migration

D : Fail safe

Answer: A,B,C

Question 5

An Architect for a multi-national transportation company has a system that is used to check the weather conditions along vehicle routes. The data is provided to drivers. The weather information is delivered regularly by a third-party company and this information is generated as JSON structure. Then the data is loaded into Snowflake in a column with a VARIANT data type. This table is directly queried to deliver the statistics to the drivers with minimum time lapse. A single entry includes (but is not limited to): - Weather condition; cloudy, sunny, rainy, etc. - Degree - Longitude and latitude - Timeframe - Location address - Wind The table holds more than 10 years' worth of data in order to deliver the statistics from different years and locations. The amount of data on the table increases every day. The drivers report that they are not receiving the weather statistics for their locations in time. What can the Architect do to deliver the statistics to the drivers faster?

A : Create an additional table in the schema for longitude and latitude. Determine a regular task to fill this information by extracting it from the JSON dataset.

B : Add search optimization service on the variant column for longitude and latitude in order to query the information by using specific metadata.

C : Divide the table into several tables for each year by using the timeframe information from the JSON dataset in order to process the queries in parallel.

D : Divide the table into several tables for each location by using the location address information from the JSON dataset in order to process the queries in parallel.

Answer: B

Page: 1 / 90

Total 449 Questions | Updated On: Dec 18, 2025

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