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Snowflake DEA-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	SnowPro Advanced: Data Engineer Certification Exam
Exam Number:	DEA-C01
Related Certifications:	SnowPro Core Certification (Recommended Prerequisite)
Exam Duration:	90 minutes
Certificate Validity Period:	2 years (recertification required)
Passing Score:	~70% (exact passing score not publicly disclosed by Snowflake)
Exam Price:	$375 USD
Available Languages:	English
Exam Format:	Multiple Select, Multiple Choice
Real Exam Qty:	approximately 50 questions
Sample Questions:	Snowflake DEA-C01 Sample Questions
Exam Way:	Online proctored exam (via Pearson VUE) or in-person testing center
Pre Condition:	SnowPro Core Certification is strongly recommended before attempting this advanced-level exam. Practical experience with Snowflake data engineering projects is essential.
Official Syllabus URL:	https://www.snowflake.com/certification/

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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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	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.
Topic 5	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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q382-Q387):

NEW QUESTION # 382
A Data Engineer executes a complex query and wants to make use of Snowflake s query results caching capabilities to reuse the results.
Which conditions must be met? (Select THREE).

A. The table structure contributing to the query result cannot have changed
B. The new query must have the same syntax as the previously executed query.
C. The query must be executed using the same virtual warehouse.
D. The micro-partitions cannot have changed due to changes to other data in the table
E. The results must be reused within 72 hours.
F. The USED_CACHED_RESULT parameter must be included in the query.

Answer: A,B,E

Explanation:
Explanation
Snowflake's query results caching capabilities allow users to reuse the results of previously executed queries without re-executing them. For this to happen, the following conditions must be met:
The results must be reused within 24 hours (not 72 hours), which is the default time-to-live (TTL) for cached results.
The query must be executed using any virtual warehouse (not necessarily the same one), as long as it is in the same region and account as the original query.
The USED_CACHED_RESULT parameter does not need to be included in the query, as it is enabled by default at the account level. However, it can be disabled or overridden at the session or statement level.
The table structure contributing to the query result cannot have changed, such as adding or dropping columns, changing data types, or altering constraints.
The new query must have the same syntax as the previously executed query, including whitespace and case sensitivity.
The micro-partitions cannot have changed due to changes to other data in the table, such as inserting, updating, deleting, or merging rows.

NEW QUESTION # 383
A data engineer needs to use an Amazon QuickSight dashboard that is based on Amazon Athena queries on data that is stored in an Amazon S3 bucket. When the data engineer connects to the QuickSight dashboard, the data engineer receives an error message that indicates insufficient permissions.
Which factors could cause to the permissions-related errors? (Choose two.)

A. QuickSight does not have access to the S3 bucket.
B. There is no IAM role assigned to QuickSight.
C. QuickSight does not have access to decrypt S3 data.
D. There is no connection between QuickSight and Athena.
E. The Athena tables are not cataloged.

Answer: A,C

NEW QUESTION # 384
Changing the retention period for your account or individual objects changes the value for all lower-level objects that do not have a retention period explicitly set?

A. TRUE
B. FALSE

Answer: A

NEW QUESTION # 385
A financial company wants to use Amazon Athena to run on-demand SQL queries on a petabyte- scale dataset to support a business intelligence (BI) application. An AWS Glue job that runs during non-business hours updates the dataset once every day. The BI application has a standard data refresh frequency of 1 hour to comply with company policies.
A data engineer wants to cost optimize the company's use of Amazon Athena without adding any additional infrastructure costs.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use the query result reuse feature of Amazon Athena for the SQL queries.
B. Change the format of the files that are in the dataset to Apache Parquet.
C. Configure an Amazon S3 Lifecycle policy to move data to the S3 Glacier Deep Archive storage class after 1 day.
D. Add an Amazon ElastiCache cluster between the BI application and Athena.

Answer: A

Explanation:
https://docs.aws.amazon.com/athena/latest/ug/performance-tuning.html
Use the Query Result Reuse Feature of Amazon Athena. This leverages Athena's built-in feature to reduce redundant data scans and thus lowers query costs.

NEW QUESTION # 386
A Data Engineer is trying to load the following rows from a CSV file into a table in Snowflake with the following structure:

....engineer is using the following COPY INTO statement:

However, the following error is received.

Which file format option should be used to resolve the error and successfully load all the data into the table?

A. ESC&PE_UNENGLO9ED_FIELD = '\\'
B. FIELD_DELIMITER = ","
C. FIELD OPTIONALLY ENCLOSED BY = " "
D. ERROR_ON_COLUMN_COUKT_MISMATCH = FALSE

Answer: C

Explanation:
Explanation
The file format option that should be used to resolve the error and successfully load all the data into the table is FIELD_OPTIONALLY_ENCLOSED_BY = '"'. This option specifies that fields in the file may be enclosed by double quotes, which allows for fields that contain commas or newlines within them. For example, in row 3 of the file, there is a field that contains a comma within double quotes: "Smith Jr., John". Without specifying this option, Snowflake will treat this field as two separate fields and cause an error due to column count mismatch. By specifying this option, Snowflake will treat this field as one field and load it correctly into the table.

NEW QUESTION # 387
......

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