Snowflake DEA-C01 Exam Questions - Easily Pass The Exam

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Snowflake DEA-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 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
  • 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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q111-Q116):

NEW QUESTION # 111
The developer team is using AWS CodeCommit for hosting private Git repositories. Developers review the code stored in this repository and merge it to the branches. The developer team wants to download code contents from a remote branch to a local repository.
What command can be used for this purpose?

Answer: A

Explanation:
The "git fetch" command will pull information about all the branches in the CodeCommit repository to the local repo.
Reference:
https://docs.aws.amazon.com/codecommit/latest/userguide/how-to-basic-git.html


NEW QUESTION # 112
A company runs a data platform on AWS. The data platform uses AWS Glue to provide a data catalog and to perform processing. The company notices quality issues in the data.
The company needs to implement data quality validations. The validations must include rules for known issues. The validations must have the ability to automatically detect unexpected data quality issues.
Which solution will meet these requirements with the LEAST operation overhead?

Answer: B

Explanation:
AWS Glue Data Quality provides native, managed data quality rules with built-in anomaly detection, allowing validation of known issues while automatically identifying unexpected data quality problems with minimal operational effort.


NEW QUESTION # 113
PARTITION_TYPE = USER_SPECIFIED must be used when you prefer to add and remove par-titions selectively rather than automatically adding partitions for all new files in an external storage location that match an expression?

Answer: A

Explanation:
Explanation
The CREATE EXTERNAL TABLE syntax for manually added partitions is as follows:
1.CREATE EXTERNAL TABLE
2.<table_name>
3.( <part_col_name> <col_type> AS <part_expr> )
4.[ , ... ]
5.[ PARTITION BY ( <part_col_name> [, <part_col_name> ... ] ) ]
6.PARTITION_TYPE = USER_SPECIFIED
Included the required PARTITION_TYPE = USER_SPECIFIED parameter.


NEW QUESTION # 114
Which of the below concepts/functions helps while implementing advanced Column-level Security?

Answer: A,C,D

Explanation:
Explanation
Column-level Security supports using Context Functions in the conditions of the masking policy body to enforce whether a user has authorization to see data. To determine whether a user can see data in a given SQL statement, it is helpful to consider:
Masking policy conditions using CURRENT_ROLE target the role in use for the current session.
Masking policy conditions using INVOKER_ROLE target the executing role in a SQL statement.
Role hierarchy
Determine if a specified role in a masking policy condition (e.g. ANALYST custom role) is a lower privilege role in the CURRENT_ROLE or INVOKER_ROLE role hierarchy. If so, then the role returned by the CURRENT_ROLE or INVOKER_ROLE functions inherits the privileges of the specified role.


NEW QUESTION # 115
A company uses a data stream in Amazon Kinesis Data Streams to collect transactional data from multiple sources. The company uses an AWS Glue extract, transform, and load (ETL) pipeline to look for outliers in the data from the stream. When the workflow detects an outlier, it sends a notification to an Amazon Simple Notification Service (Amazon SNS) topic. The SNS topic initiates a second workflow to retrieve logs for the outliers and stores the logs in an Amazon S3 bucket.
The company experiences delays in the notifications to the SNS topic during periods when the data stream is processing a high volume of data. When the company examines Amazon CloudWatch logs, the company notices a high value for the glue.driver.BlockManager.disk.diskSpaceUsed_MB metric when the traffic is high. The company must resolve this issue.
Which solution will meet this requirement with the LEAST operational effort?

Answer: B

Explanation:
The high BlockManager disk usage indicates memory pressure and spilling due to under- provisioned Spark executors. Enabling AWS Glue auto scaling lets the job automatically add workers during traffic spikes, alleviating memory/disk pressure and reducing delays with minimal operational effort.


NEW QUESTION # 116
......

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