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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q12-Q17):

NEW QUESTION # 12
Which Role inherits the privileges of the USERADMIN role via the system role hierarchy?

  • A. PUBLIC
  • B. SYSADMIN
  • C. CUSTOM ROLE
  • D. SECURITYADMIN

Answer: D


NEW QUESTION # 13
In Which Data Modelling Technique, Data Engineer generally refer the terms Hubs & Satellites?

  • A. Data Vault
  • B. Star Schema
  • C. Snowflake Schema
  • D. Data Hub

Answer: A

Explanation:
Explanation
In Data Vault modelling, Hubs are entities of interest to the business.
They contain just a distinct list of business keys and metadata about when each key was first loaded and from where.
In Data Vault modelling, Satellites connect to Hubs or Links. They are Point in Time: so we can ask and answer the question, "what did we know when?" Satellites contain data about their parent Hub or Link and metadata about when the data was load-ed, from where, and a business effectivity date.


NEW QUESTION # 14
Select the correct usage statements with regards to SQL UDF?

  • A. You can include only one query expression.
  • B. When using a query expression in a SQL UDF, do not include a semicolon within the UDF body to terminate the query expression.
  • C. All of above are correct.
  • D. The body of a UDF cannot contain DDL statements or any DML statement other than SELECT.
  • E. Scalar functions (UDFs) have a limit of 500 input arguments.

Answer: C


NEW QUESTION # 15
Which ones are the false statements about Materialized Views?

  • A. Snowflake does not allow users to truncate materialized views.
  • B. Materialized views can be secure views.
  • C. Clustering a subset of the materialized views on a table tends to be more cost-effective than clustering the table itself.
  • D. Materialized views are first-class account objects.
  • E. Snowflake does not allow standard DML (e.g. INSERT, UPDATE, DELETE) on ma-terialized views.
  • F. A materialized view can also be used as the data source for a subquery.

Answer: D

Explanation:
Explanation
Materialized views are first-class Database objects & rest of the understandings are true.


NEW QUESTION # 16
Which connector creates the RECORD_CONTENT and RECORD_METADATA columns in the existing Snowflake table while connecting to Snowflake?

  • A. Python Connector
  • B. Node.js connector
  • C. Spark Connector
  • D. Kafka Connector

Answer: D

Explanation:
Explanation
Apache Kafka software uses a publish and subscribe model to write and read streams of records, similar to a message queue or enterprise messaging system. Kafka allows processes to read and write messages asynchronously. A subscriber does not need to be connected directly to a publisher; a pub-lisher can queue a message in Kafka for the subscriber to receive later.
An application publishes messages to a topic, and an application subscribes to a topic to receive those messages. Kafka can process, as well as transmit, messages; however, that is outside the scope of this document. Topics can be divided into partitions to increase scalability.
Kafka Connect is a framework for connecting Kafka with external systems, including databases. A Kafka Connect cluster is a separate cluster from the Kafka cluster. The Kafka Connect cluster sup-ports running and scaling out connectors (components that support reading and/or writing between external systems).
The Kafka connector is designed to run in a Kafka Connect cluster to read data from Kafka topics and write the data into Snowflake tables.
Every Snowflake table loaded by the Kafka connector has a schema consisting of two VARIANT columns:
RECORD_CONTENT. This contains the Kafka message.
RECORD_METADATA. This contains metadata about the message, for example, the topic from which the message was read.


NEW QUESTION # 17
......

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