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Each format has a pool of SnowPro Advanced: Data Engineer Certification Exam (DEA-C01) actual questions which have been compiled under the guidance of thousands of professionals worldwide. Questions in this product will appear in the Snowflake DEA-C01 final test. Hence, memorizing them will help you get prepared for the DEA-C01 examination in a short time. The product of ITPassLeader comes in PDF, desktop practice exam software, and DEA-C01 web-based practice test. To give you a complete understanding of these formats, we have discussed their features below.

Snowflake DEA-C01 Exam Overview:

Certification Vendor:Snowflake
Exam Name:SnowPro Advanced: Data Engineer Certification Exam
Exam Number:DEA-C01
Real Exam Qty:approximately 50 questions
Related Certifications:SnowPro Core Certification (Recommended Prerequisite)
Exam Price:$375 USD
Exam Duration:90 minutes
Passing Score:~70% (exact passing score not publicly disclosed by Snowflake)
Exam Format:Multiple Choice, Multiple Select
Available Languages:English
Certificate Validity Period:2 years (recertification required)
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:

TopicDetails
Topic 1
  • 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 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
  • 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 4
  • 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 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 (Q364-Q369):

NEW QUESTION # 364
Data Engineer is using existing pipe that automates data loads using event notifications, later he figured out the needs to modify pipe properties. For the same, He decided to recreate the pipe as best practice. He followed the below steps for the same.
1. Query the SYSTEM$PIPE_STATUS function and verify that the pipe execution state is RUN-NING.
2. Recreate the pipe (using CREATE OR REPLACE PIPE).
3. Query the SYSTEM$PIPE_STATUS function and verify that the pipe execution state is RUN-NING.
Which are the Missing recommended steps while Recreating Pipes for Automated Data Loads?

Answer: B

Explanation:
Explanation
Recreating a pipe (using a CREATE OR REPLACE PIPE statement) is necessary to modify most pipe properties.
Recreating Pipes for Automated Data Loads
When recreating a pipe that automates data loads using event notifications, it's recommended that Data Engineer complete the following steps:
1. Pause the pipe (using ALTER PIPE ... SET PIPE_EXECUTION_PAUSED = true).
2. Query the SYSTEM$PIPE_STATUS function and verify that the pipe execution state is PAUSED.
3. Recreate the pipe (using CREATE OR REPLACE PIPE).
4. Pause the pipe again.
5. Review the configuration steps for your cloud messaging service to ensure the settings are still accurate.
6. Query the SYSTEM$PIPE_STATUS function again and verify that the pipe execution state is RUNNING.


NEW QUESTION # 365
A Data Engineer ran a stored procedure containing various transactions During the execution, the session abruptly disconnected preventing one transactionfrom committing or rolling hark.The transaction was left in a detached state and created a lock on resources
...must the Engineer take to immediately run a new transaction?

Answer: A

Explanation:
Explanation
The system function SYSTEM$ABORT_TRANSACTION can be used to abort a detached transaction that was left in an open state due to a session disconnect or termination. The function takes one argument: the transaction ID of the detached transaction. The function will abort the transaction and release any locks held by it. The other options are incorrect because they do not address the issue of a detached transaction. The system function SYSTEM$CANCEL_TRANSACTION can be used to cancel a running transaction, but not a detached one. The LOCK_TIMEOUT parameter can be used to set a timeout period for acquiring locks on resources, but it does not affect existing locks. The TRANSACTION_ABORT_ON_ERROR parameter can be used to control whether a transaction should abort or continue when an error occurs, but it does not affect detached transactions.


NEW QUESTION # 366
In data modeling, an entity-relationship diagram (ERD) is primarily used to:

Answer: C


NEW QUESTION # 367
A university is developing an educational application that analyzes student essays. The application provides personalized feedback with accurate citations to the university's textbooks.
The application needs to process essays in multiple languages. Application responses must include direct references to specific sections in the course materials and must be in the student's selected language. Which solution will meet these requirements with the LEAST operational overhead?

Answer: B

Explanation:
Amazon Bedrock Knowledge Bases is the lowest-overhead solution because it provides a managed retrieval-augmented generation workflow over the university's textbooks and can return generated responses with citations to the source material. The RetrieveAndGenerate capability is designed to generate answers from retrieved textbook content and include source citations, which directly matches the requirement for accurate references to specific course materials. By choosing a multilingual model in Bedrock for generation, the application can respond in the student's selected language without building and operating a custom retrieval stack.
Reference:
https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base.html
https://docs.aws.amazon.com/bedrock/latest/userguide/kb-test-retrieve-generate.html
https://docs.aws.amazon.com/bedrock/latest/userguide/kb-how-retrieval.html


NEW QUESTION # 368
Which functions will compute a 'fingerprint' over an entire table, query result, or window to quickly detect changes to table contents or query results? (Select TWO).

Answer: A,C

Explanation:
Explanation
The functions that will compute a 'fingerprint' over an entire table, query result, or window to quickly detect changes to table contents or query results are:
HASH_AGG(*): This function computes a hash value over all columns and rows in a table, query result, or window. The function returns a single value for each group defined by a GROUP BY clause, or a single value for the entire input if no GROUP BY clause is specified.
HASH_AGG(<expr>, <expr>): This function computes a hash value over two expressions in a table, query result, or window. The function returns a single value for each group defined by a GROUP BY clause, or a single value for the entire input if no GROUP BY clause is specified. The other functions are not correct because:
HASH (*): This function computes a hash value over all columns in a single row. The function returns one value per row, not one value per table, query result, or window.
HASH_AGG_COMPARE (): This function compares two hash values computed by HASH_AGG() over two tables or query results and returns true if they are equal or false if they are different. The function does not compute a hash value itself, but rather compares two existing hash values.
HASH COMPARE(): This function compares two hash values computed by HASH() over two rows and returns true if they are equal or false if they are different. The function does not compute a hash value itself, but rather compares two existing hash values.


NEW QUESTION # 369
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