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Free SNOWPRO-ADVANCED-ARCHITECT – Snowflake SNOWPRO-ADVANCED-ARCHITECT Practice Test Question

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Showing 16–18 of 20 questions

Question 16 (Topic 1)

A table, contacts_data, is created and data is inserted into it: create table contacts_data (c object); Insert into contacts_data - select parse_json (' { "customer”: { "address": "509 Kings Hwy, Comptche, Missouri, 4848", "phone": "+1 (999) 407-2274", "email": " [email protected] ", "company": "SNOWFLAKE", "name": { "last": "Person", "first": "Snow" }, "_id": "5730864df388fld653e37e6f" } } '); Which queries will retrieve the first name value as Snow? (Choose two.)

Select an option, then click Submit answer.

  • ○ select o[customer][name][first]::string as first_name from contacts_data;
  • ○ select o['customer']['name']['first']::string as first_name from contacts_data;
  • ○ select o:['customer']:['name']:['first']::string as first_name from contacts_data;
  • ○ select 0:Customer.Name.First::string as first_name from contacts_data;
  • ○ select 0:customer.name.first::string as first_name from contacts_data;
Question 17 (Topic 1)

A company is considering adopting Data Mesh as their data platform architecture. Which Snowflake features and services offer native support of this architecture? (Choose three.)

Select an option, then click Submit answer.

  • ○ Isolated compute and shared storage allowing data teams to manage their own workloads.
  • ○ Data sharing, the Snowflake Marketplace, and the Data Exchange supporting the Data Mesh publish-and-serve model.
  • ○ Dynamic Data Masking ensuring that data is always masked with hashing functions.
  • ○ Materialized views supporting that external tables in the mesh are visible from all databases and accounts.
  • ○ Built-In data governance managing the visibility and accessibility of data product components.
  • ○ Federated authentication supporting external user access to Snowflake data products accounts.
Question 18 (Topic 1)

A company’s table, employees, was replaced with a new version: How can the original table be recovered with the LEAST operational overhead?

Select an option, then click Submit answer.

  • ○ Use Time Travel to recover the data using this command: SELECT * FROM employees BEFORE(statement => ‘01a5c8b3-0601-ad2b-0067-a503000al312’);
  • ○ Use Time Travel with the timestamp to recover the data using this command: SELECT * FROM employees AT(timestamp => ‘2022-07-22 16:35:00.000 -0700’::timestamp_tz);
  • ○ Revert to the original employees table using this command: UNDROP TABLE employees;
  • ○ Rename the new employees table and undrop the original employees table using this command: ALTER TABLE employees rename to employees_bad; UNDROP TABLE employees;