Pass Guaranteed Quiz DEA-C01 - SnowPro Advanced: Data Engineer Certification Exam–Valid Dumps Guide

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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Data Transformation: The SnowPro Advanced: Data Engineer exam evaluates skills in using User-Defined Functions (UDFs), external functions, and stored procedures. It assesses the ability to handle semi-structured data and utilize Snowpark for transformations. This section ensures Snowflake engineers can effectively transform data within Snowflake environments, critical for data manipulation tasks.
Topic 2	Data Movement: Snowflake Data Engineers and Software Engineers are assessed on their proficiency to load, ingest, and troubleshoot data in Snowflake. It evaluates skills in building continuous data pipelines, configuring connectors, and designing data sharing solutions.
Topic 3	Security: The Security topic of the DEA-C01 test covers the principles of Snowflake security, including the management of system roles and data governance. It measures the ability to secure data and ensure compliance with policies, crucial for maintaining secure data environments for Snowflake Data Engineers and Software Engineers.
Topic 4	Storage and Data Protection: The topic tests the implementation of data recovery features and the understanding of Snowflake's Time Travel and micro-partitions. Engineers are evaluated on their ability to create new environments through cloning and ensure data protection, highlighting essential skills for maintaining Snowflake data integrity and accessibility.
Topic 5	Performance Optimization: This topic assesses the ability to optimize and troubleshoot underperforming queries in Snowflake. Candidates must demonstrate knowledge in configuring optimal solutions, utilizing caching, and monitoring data pipelines. It focuses on ensuring engineers can enhance performance based on specific scenarios, crucial for Snowflake Data Engineers and Software Engineers.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q83-Q88):

NEW QUESTION # 83
What kind of Snowflake integration is required when defining an external function in Snowflake?

A. Security integration
B. API integration
C. HTTP integration
D. Notification integration

Answer: B

Explanation:
Explanation
An API integration is required when defining an external function in Snowflake. An API integration is a Snowflake object that defines how Snowflake communicates with an externalservice via HTTPS requests and responses. An API integration specifies parameters such as URL, authentication method, encryption settings, request headers, and timeout values. An API integration is used to create an external function object that invokes the external service from within SQL queries.

NEW QUESTION # 84
Which are the Cloud Platforms that Support Calling an External Function?

A. AWS,GCP,AZURE
B. GCP
C. AWS only
D. AWS & AZURE

Answer: A

NEW QUESTION # 85
Select the incorrect statements regarding Clustering depth?

A. It helps Monitoring the clustering "health" of a large table, particularly over time as DML is performed on the table.
B. A table with no micro-partitions (i.e. an unpopulated/empty table) has a clustering depth of 1.
(Correct)
C. The clustering depth for a populated table measures the average depth (1 or greater) of the overlapping micro-partitions for specified columns in a table. The smaller the aver-age depth, the better clustered the table is with regards to the specified columns.
D. Clustering depth can be used for determining whether a large table would benefit from explicitly defining a clustering key.

Answer: B

Explanation:
Explanation
A table with no micro-partitions (i.e. an unpopulated/empty table) has a clustering depth of 0.

NEW QUESTION # 86
Data Engineer identified use case where he decided to use materialized view for query perfor-mance. Which one is not the limitation he must be aware of before using MVs in their use case?

A. A materialized view cannot include HAVING clauses OR ORDER BY clause.
B. Truncating a materialized view is not supported.
C. Context Functions like CURRENT_TIME or CURRENT_TIMESTAMP is not per-mitted.
D. A materialized view can query only a single table & Joins, including self-joins, are not supported.
E. You cannot directly clone a materialized view by using the CREATE MATERIAL-IZED VIEW ...
CLONE... command.
F. A materialized views does not support clustering.
G. Time Travel is not currently supported on materialized views.
H. A materialized views cannot be created on Shared Data.

Answer: A,F

Explanation:
Explanation
Defining a clustering key on a materialized view is supported and can increase performance in many situations. However, it also adds costs.
If you cluster both the materialized view(s) and the base table on which the materialized view(s) are defined, you can cluster the materialized view(s) on different columns from the columns used to cluster the base table.
You can create a materialized view on shared data.
Also You can use Snowflake's data sharing feature to share a materialized view.
Rest all are correct.

NEW QUESTION # 87
Which column provides information when the stream became stale or may become stale if not con-sumed?

A. STREAM_STALE_PERIOD
B. STALE_PERIOD_AFTER
C. STALE_STREAM_PERIOD
D. STALE_AFTER

Answer: D

Explanation:
Explanation
execute SHOW STREAMS command.
Column Name: STALE_AFTER
Timestamp when the stream became stale or may become stale if not consumed. The value is calcu-lated by adding the retention period for the source table (i.e. the larger of the DA-TA_RETENTION_TIME_IN_DAYS or MAX_DATA_EXTENSION_TIME_IN_DAYS parame-ter setting) to the last time the stream was read.

NEW QUESTION # 88
......

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