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Snowflake DEA-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	SnowPro Advanced: Data Engineer Certification Exam
Exam Number:	DEA-C01
Available Languages:	Japanese, English
Exam Duration:	115 minutes
Real Exam Qty:	65
Exam Format:	Multiple select, Multiple choice
Certificate Validity Period:	2 years
Exam Price:	$375 USD
Passing Score:	750 / 1000
Related Certifications:	SnowPro Advanced: Security Engineer SnowPro Advanced: Data Analyst SnowPro Advanced: Data Scientist SnowPro Advanced: Architect SnowPro Advanced: Administrator SnowPro Core
Recommended Training:	SnowPro Advanced: Data Engineer Exam Study Guide Snowflake University Training Courses
Exam Registration:	Snowflake Certification Portal Pearson VUE Registration
Sample Questions:	Snowflake DEA-C01 Sample Questions
Exam Way:	Online proctored or onsite at Pearson VUE test centers
Pre Condition:	Must hold active SnowPro Core Certification; recommended 2+ years hands-on data engineering experience
Official Syllabus URL:	https://learn.snowflake.com/en/certifications/snowpro-advanced-dataengineer/

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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	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 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	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 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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q384-Q389):

NEW QUESTION # 384
An online retailer uses multiple delivery partners to deliver products to customers. The delivery partners send order summaries to the retailer. The retailer stores the order summaries in Amazon S3.
Some of the order summaries contain personally identifiable information (PII) about customers. A data engineer needs to detect PII in the order summaries so the company can redact the PII.
Which solution will meet these requirements with the LEAST operational overhead?

A. Amazon Textract
B. Amazon S3 Storage Lens
C. Amazon SageMaker Data Wrangler
D. Amazon Macie

Answer: D

Explanation:
Amazon Macie is a fully managed data security and privacy service that uses machine learning and pattern matching to discover and protect sensitive data, such as Personally Identifiable Information (PII), stored in Amazon S3. Macie can automatically scan the order summaries for PII, enabling the company to detect and then redact PII as required.

NEW QUESTION # 385
A company plans to provision a log delivery stream within a VPC. The company configured the VPC flow logs to publish to Amazon CloudWatch Logs. The company needs to send the flow logs to Splunk in near real time for further analysis.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create an Amazon Kinesis Data Firehose delivery stream to use Splunk as the destination. Create an AWS Lambda function to send the flow logs from CloudWatch Logs to the delivery stream.
B. Configure an Amazon Kinesis Data Streams data stream to use Splunk as the destination. Create a CloudWatch Logs subscription filter to send log events to the data stream.
C. Create an Amazon Kinesis Data Firehose delivery stream to use Splunk as the destination. Create a CloudWatch Logs subscription filter to send log events to the delivery stream.
D. Configure an Amazon Kinesis Data Streams data stream to use Splunk as the destination. Create an AWS Lambda function to send the flow logs from CloudWatch Logs to the data stream.

Answer: C

Explanation:
Kinesis Data Firehose has built-in support for Splunk as a destination, making the integration straightforward. Using a CloudWatch Logs subscription filter directly to Firehose simplifies the data flow, eliminating the need for additional Lambda functions or custom integrations.

NEW QUESTION # 386
Two data engineering teams use separate AWS accounts. Both teams request access to the same datashare in an Amazon Redshift cluster that is in a third AWS account. The datashare is named salesshare.
A data engineer must use the Amazon Redshift SQL interface to grant both data engineering teams' access to the datashare.
Which command or commands will meet this requirement?

A. GRANT USAGE ON DATASHARE salesshare TO ACCOUNTS '<account ID 1>' AND '<account ID 2>';
B. GRANT USAGE ON DATASHARE salesshare TO NAMESPACES '<account ID 1>' AND
'<account ID 2>';
C. GRANT USAGE ON DATASHARE salesshare TO ACCOUNT '<account ID 1>';
GRANT USAGE ON DATASHARE salesshare TO ACCOUNT '<account ID 2>';
D. GRANT USAGE ON DATASHARE salesshare TO NAMESPACE '<account ID 1>';
GRANT USAGE ON DATASHARE salesshare TO NAMESPACE '<account ID 2>';

Answer: D

Explanation:
In Amazon Redshift data sharing, cross-account permissions for a datashare are granted to consumer cluster/serverless namespaces. Granting USAGE on the datashare to each consumer namespace enables both teams' Redshift environments in their respective accounts to create and query databases from the shared data.

NEW QUESTION # 387
Mark the incorrect statement in case Data engineer using the COPY INTO <table> command to load data from files into Snowflake tables?

A. For loading data from all semi-structured supported file formats (JSON, Avro, etc.), as well as unloading data, UTF-8 is the only supported character set.
B. For Data loading of files with semi-structured file formats (JSON, Avro, etc.), the only supported character set is UTF-16.
C. For Local environment, Files are first copied ("staged") to an internal (Snowflake) stage, then loaded into a table.
D. UTF-32 & UTF-16 both encoding character sets supported for loading data from de-limited files (CSV, TSV, etc.)

Answer: B

Explanation:
Explanation
For Data Loading of delimited files (CSV, TSV, etc.), the default character set is UTF-8. To use any other characters sets, you must explicitly specify the encoding to use for loading.
For semi-structured file formats (JSON, Avro, etc.), the only supported character set is UTF-8.
Rest of the statements are correct.

NEW QUESTION # 388
A SQL UDF evaluates an arbitrary SQL expression and returns the result(s) of the expression. Which value type it can returns?

A. Single Value
B. Scaler or Tabular depend on input SQL expression
C. Regex
D. A Set of Rows

Answer: B

NEW QUESTION # 389
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