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Snowflake DEA-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	SnowPro Advanced: Data Engineer Certification Exam
Exam Number:	DEA-C01
Real Exam Qty:	Approximately 65 questions
Passing Score:	Not publicly disclosed (Snowflake uses scaled scoring)
Available Languages:	English
Exam Duration:	115 minutes
Related Certifications:	SnowPro Core Certification
Exam Price:	$375 USD
Certificate Validity Period:	2 years
Exam Format:	Multiple choice, Scenario-based questions, Multiple select
Recommended Training:	Snowflake University Training SnowPro Advanced Data Engineer Exam Guide
Exam Registration:	Snowflake Certification Portal
Sample Questions:	Snowflake DEA-C01 Sample Questions
Exam Way:	Online proctored or authorized testing center
Pre Condition:	Recommended: SnowPro Core Certification or equivalent Snowflake experience
Official Syllabus URL:	https://www.snowflake.com/certifications/snowpro-advanced-data-engineer/

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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	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 3	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 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 (Q129-Q134):

NEW QUESTION # 129
A company needs to aggregate and filter a large amount of streaming data in real-time with low latency. The company needs to store the data in Amazon S3 for analysis.
Which solution will meet these requirements in the MOST operationally efficient way?

A. Use Amazon Kinesis Data Streams and Amazon Managed Service for Apache Flink to perform complex processing and to integrate with Amazon S3.
B. Use Amazon Data Firehose with built-in data transformations. Deliver the data directly to Amazon S3.
C. Use Amazon Kinesis Data Streams with provisioned capacity and AWS Lambda functions to perform custom transformations and to integrate with Amazon S3.
D. Use Amazon Data Firehose and AWS Lambda functions to perform custom transformations and to deliver the data to Amazon S3.

Answer: A

Explanation:
Amazon Kinesis Data Streams with Amazon Managed Service for Apache Flink performs stateful, low-latency streaming aggregations and filtering at scale, then writes results to Amazon S3 - meeting real-time requirements while remaining fully managed and operationally efficient.

NEW QUESTION # 130
Let us say you have List of 50 Source files, which needs to be loaded into Snowflake internal stage. All these Source system files are already Brotli-compressed files. Which statement is correct with respect to Compression of Staged Files?

A. Snowflake automatically detect Brotli Compression, will skip further compression of all 50 files.
B. Even though Source files are already compressed, Snowflake do apply default gzip2 Compression to optimize the storage cost.
C. When staging 50 compressed files in a Snowflake stage, the files are automatically com-pressed using gzip.
D. Auto-detection is not yet supported for Brotli-compressed files; when staging or loading Brotli-compressed files, you must explicitly specify the compression method that was used.

Answer: D

Explanation:
Explanation
Auto-detection is not yet supported for Brotli-compressed files; when staging or loading Brotli-compressed files, you must explicitly specify the compression method that was used.
To Know more about Compression of Staged Files, please refer the link:
https://docs.snowflake.com/en/user-guide/intro-summary-loading.html#compression-of-staged-files

NEW QUESTION # 131
A company stores data in a data lake that is in Amazon S3. Some data that the company stores in the data lake contains personally identifiable information (PII). Multiple user groups need to access the raw data. The company must ensure that user groups can access only the PII that they require.
Which solution will meet these requirements with the LEAST effort?

A. Build a custom query builder UI that will run Athena queries in the background to access the data.
Create user groups in Amazon Cognito. Assign access levels to the user groups based on the PII access requirements of the users.
B. Use Amazon QuickSight to access the data. Use column-level security features in QuickSight to limit the PII that users can retrieve from Amazon S3 by using Amazon Athena. Define QuickSight access levels based on the PII access requirements of the users.
C. Create IAM roles that have different levels of granular access. Assign the IAM roles to IAM user groups. Use an identity-based policy to assign access levels to user groups at the column level.
D. Use Amazon Athena to query the data. Set up AWS Lake Formation and create data filters to establish levels of access for the company's IAM roles. Assign each user to the IAM role that matches the user's PII access requirements.

Answer: D

Explanation:
https://aws.amazon.com/blogs/big-data/anonymize-and-manage-data-in-your-data-lake-with- amazon-athena-and-aws-lake-formation/

NEW QUESTION # 132
What are Invalid rules applicable when using stored procedure contains transaction?

A. If a transaction is started inside a stored procedure and is still active when the stored procedure finishes, then an error occurs, and the transaction is rolled back.
B. You cannot start a transaction before calling the stored procedure, then complete the transaction inside the stored procedure.
C. A transaction can be inside a stored procedure, or a stored procedure can be inside a transaction.
D. All Rules are Applicable.
E. A transaction inside a stored procedure can include a call to another stored procedure that contains a transaction.
F. You cannot start a transaction inside the stored procedure, then complete the transac-tion after returning from the procedure.

Answer: D

NEW QUESTION # 133
A data engineer needs to design a data pipeline that invokes an AWS Glue job. After the AWS Glue job finishes successfully, the pipeline needs to invoke three AWS Lambda functions. The pipeline must be serverless. The data engineer wants to see the entire pipeline lineage in a single interface.
Which solution will meet these requirements?

A. Configure a workflow in AWS Step Functions that invokes the AWS Glue job and the Lambda functions. View the lineage in Step Functions Workflow Studio.
B. Build the pipeline in the AWS Glue job. Invoke the Lambda functions after the AWS Glue job runs.
Use Amazon CloudWatch Logs Insights to view the lineage.
C. Deploy an Apache Airflow workflow that invokes the AWS Glue job and the Lambda functions.
View the lineage in the Airflow UI.
D. Deploy a workflow in AWS Step Functions to invoke the AWS Glue job. In the job code, invoke the Lambda functions before the job finishes. View the lineage from the AWS Glue UI.

Answer: A

Explanation:
AWS Step Functions is a fully serverless orchestration service that can coordinate an AWS Glue job and then invoke multiple Lambda functions after the job succeeds. It provides a single visual interface for the full workflow, making it easy to trace each step of the pipeline lineage in one place.

NEW QUESTION # 134
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