Snowflake ARA-C01 Exam Dumps - Updated Apr 2024

An Architect needs to design a data unloading strategy for Snowflake, that will be used with the COPY INTO command.

Which configuration is valid?

ALocation of files: Snowflake internal location
. File formats: CSV, XML
. File encoding: UTF-8
. Encryption: 128-bit

BLocation of files: Amazon S3
. File formats: CSV, JSON
. File encoding: Latin-1 (ISO-8859)
. Encryption: 128-bit

CLocation of files: Google Cloud Storage
. File formats: Parquet
. File encoding: UTF-8
* Compression: gzip

DLocation of files: Azure ADLS
. File formats: JSON, XML, Avro, Parquet, ORC
. Compression: bzip2
. Encryption: User-supplied key

Question 2

Which command will create a schema without Fail-safe and will restrict object owners from passing on access to other users?

Acreate schema EDW.ACCOUNTING WITH MANAGED ACCESS;

Bcreate schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS - 7;

Ccreate TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 1;

Dcreate TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 7;

Question 3

A company is designing a process for importing a large amount of loT JSON data from cloud storage into Snowflake. New sets of loT data get generated and uploaded approximately every 5 minutes.

Once the loT data is in Snowflake, the company needs up-to-date information from an external vendor to join to the dat

a. This data is then presented to users through a dashboard that shows different levels of aggregation. The external vendor is a Snowflake customer.

What solution will MINIMIZE complexity and MAXIMIZE performance?

A1. Create an external table over the JSON data in cloud storage.
2. Create a task that runs every 5 minutes to run a transformation procedure on new data, based on a saved timestamp.
3. Ask the vendor to expose an API so an external function can be used to generate a call to join the data back to the loT data in the transformation procedure.
4. Give the transformed table access to the dashboard tool.
5. Perform the aggregations on the dashboard tool.

B1. Create an external table over the JSON data in cloud storage.
2. Create a task that runs every 5 minutes to run a transformation procedure on new data based on a saved timestamp.
3. Ask the vendor to create a data share with the required data that can be imported into the company's Snowflake account.
4. Join the vendor's data back to the loT data using a transformation procedure.
5. Create views over the larger dataset to perform the aggregations required by the dashboard.
6. Give the views access to the dashboard tool.

C1. Create a Snowpipe to bring the JSON data into Snowflake.
2. Use streams and tasks to trigger a transformation procedure when new JSON data arrives.
3. Ask the vendor to expose an API so an external function call can be made to join the vendor's data back to the loT data in a transformation procedure.
4. Create materialized views over the larger dataset to perform the aggregations required by the dashboard.
5. Give the materialized views access to the dashboard tool.

D1. Create a Snowpipe to bring the JSON data into Snowflake.
2. Use streams and tasks to trigger a transformation procedure when new JSON data arrives.
3. Ask the vendor to create a data share with the required data that is then imported into the Snowflake account.
4. Join the vendor's data back to the loT data in a transformation procedure
5. Create materialized views over the larger dataset to perform the aggregations required by the dashboard.
6. Give the materialized views access to the dashboard tool.

Question 4

A retailer's enterprise data organization is exploring the use of Data Vault 2.0 to model its data lake solution. A Snowflake Architect has been asked to provide recommendations for using Data Vault 2.0 on Snowflake.

What should the Architect tell the data organization? (Select TWO).

AChange data capture can be performed using the Data Vault 2.0 HASH_DIFF concept.

BChange data capture can be performed using the Data Vault 2.0 HASH_DELTA concept.

CUsing the multi-table insert feature in Snowflake, multiple Point-in-Time (PIT) tables can be loaded in parallel from a single join query from the data vault.

DUsing the multi-table insert feature, multiple Point-in-Time (PIT) tables can be loaded sequentially from a single join query from the data vault.

EThere are performance challenges when using Snowflake to load multiple Point-in-Time (PIT) tables in parallel from a single join query from the data vault.

Question 5

What is the MOST efficient way to design an environment where data retention is not considered critical, and customization needs are to be kept to a minimum?

AUse a transient database.

BUse a transient schema.

CUse a transient table.

DUse a temporary table.

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