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Which query will identify the specific days and virtual warehouses that would benefit from a multi-cluster warehouse to improve the performance of a particular workload?

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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 data. 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?

• A. 1. 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.
• B. 1. 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 procedure5. 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.
• C. 1. 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.
• D. 1. 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.

Role A has the following permissions:
. USAGE on db1
. USAGE and CREATE VIEW on schemal in db1
. SELECT on tablel in schemal
Role B has the following permissions:
. USAGE on db2
. USAGE and CREATE VIEW on schema2 in db2
. SELECT on table2 in schema2
A user has Role A set as the primary role and Role B as a secondary role.
What command will fail for this user?

• A. use database db2;use schema schema2;select * from db1.schemal.tablel union select * from table2;
• B. use database db2;use schema schema2;create view v2 as select * from dbl.schemal. tablel;
• C. use database db1;use schema schemal;create view v1 as select * from db2.schema2.table2;
• D. use database db1;use schema schemal;select * from db2.schema2.table2;

A company's client application supports multiple authentication methods, and is using Okta.
What is the best practice recommendation for the order of priority when applications authenticate to Snowflake?

• A. 1) Okta native authentication2) Key Pair Authentication, mostly used for production environment users3) Password4) OAuth (either Snowflake OAuth or External OAuth)5) External browser, SSO
• B. 1) OAuth (either Snowflake OAuth or External OAuth)2) External browser3) Okta native authentication4) Key Pair Authentication, mostly used for service account users5) Password
• C. 1) External browser, SSO2) Key Pair Authentication, mostly used for development environment users3) Okta native authentication4) OAuth (ether Snowflake OAuth or External OAuth)5) Password
• D. 1) Password2) Key Pair Authentication, mostly used for production environment users3) Okta native authentication4) OAuth (either Snowflake OAuth or External OAuth)5) External browser, SSO

The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1) Finance and Vendor Management team members who require reporting and visualization
2) Data Science team members who require access to raw data for ML model development
3) Sales team members who require engineered and protected data for data monetization What Snowflake data modeling approaches will meet these requirements? (Choose two.)

• A. Consolidate data in the company's data lake and use EXTERNAL TABLES.
• B. Create a raw database for landing and persisting raw data entering the data pipelines.
• C. Create a single star schema in a single database to support all consumers' requirements.
• D. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.
• E. Create a set of profile-specific databases that aligns data with usage patterns.