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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)
Passing Score:	~70% (exact passing score not publicly disclosed by Snowflake)
Real Exam Qty:	approximately 50 questions
Exam Duration:	90 minutes
Available Languages:	English
Exam Price:	$375 USD
Certificate Validity Period:	2 years (recertification required)
Exam Format:	Multiple Choice, Multiple Select
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	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	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	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	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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q75-Q80):

NEW QUESTION # 75
A company that operates globally must follow regulations that require data from an AWS Region to be accessible only within that Region.
A data engineer is creating a data pipeline that will create resources in the Region where the data engineer works. The data pipeline should have access to data only from the Region where the data engineer works. The pipeline uses Active Directory as an identity and authentication system.
The pipeline uses a custom identity broker application to verify that employees are signed in to Active Directory and to obtain temporary credentials by using the AssumeRole API operation.
Which solution will meet the locality requirements with the LEAST administrative effort?

A. Create individual IAM policies that allow users to create resources in a specific Region. Assign the policies to each data engineer. Allow users to assume the individually assigned role when the users log in to AWS.
B. Create an IAM role for data engineers in each Region separately. Instruct each data engineer to obtain temporary credentials by assuming the appropriate Region specific IAM role.
C. Create an IAM role that has permissions to create resources. Create a policy for each Region that ensures users can create resources only in that Region. Pass the policy as the session policy when employees obtain the temporary credentials.
D. Create an IAM group for each Region. Include the required IAM policies for each IAM group. Add users to each IAM group so that when users log in by obtaining the temporary credentials, the users will receive the appropriate access based on the IAM group.

Answer: C

Explanation:
Using a single IAM role with region-scoped session policies (using the aws:RequestedRegion condition) applied at AssumeRole time lets the identity broker grant temporary credentials limited to the engineer's Region. This enforces Regional access while avoiding per-Region roles or per- user policies, minimizing administration.

NEW QUESTION # 76
A marketing company collects clickstream data. The company sends the clickstream data to Amazon Kinesis Data Firehose and stores the clickstream data in Amazon S3. The company wants to build a series of dashboards that hundreds of users from multiple departments will use.
The company will use Amazon QuickSight to develop the dashboards. The company wants a solution that can scale and provide daily updates about clickstream activity.
Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.)

A. Use Amazon Redshift to store and query the clickstream data.
B. Use Amazon Athena to query the clickstream data
C. Access the query data through a QuickSight direct SQL query.
D. Access the query data through QuickSight SPICE (Super-fast, Parallel, In-memory Calculation Engine). Configure a daily refresh for the dataset.
E. Use Amazon S3 analytics to query the clickstream data.

Answer: B,D

Explanation:
Athena would be cheaper than Redshift. S3 analytics is irrelevant. The functionality in SPICE should be more cost effective than direct SQL by reducing the frequency and volume of queries.

NEW QUESTION # 77
A company has a data lake on AWS. The data lake ingests sources of data from business units.
The company uses Amazon Athena for queries. The storage layer is Amazon S3 with an AWS Glue Data Catalog as a metadata repository.
The company wants to make the data available to data scientists and business analysts.
However, the company first needs to manage fine-grained, column-level data access for Athena based on the user roles and responsibilities.
Which solution will meet these requirements?

A. Define an IAM resource-based policy for AWS Glue tables. Attach the same policy to IAM user groups.
B. Define an IAM identity-based policy for AWS Glue tables. Attach the same policy to IAM roles.
Associate the IAM roles with IAM groups that contain the users.
C. Create a resource share in AWS Resource Access Manager (AWS RAM) to grant access to IAM users.
D. Set up AWS Lake Formation. Define security policy-based rules for the users and applications by IAM role in Lake Formation.

Answer: D

Explanation:
Lake Formation supports fine-grained access control, including column-level permissions.

NEW QUESTION # 78
An insurance company stores transaction data that the company compressed with gzip.
The company needs to query the transaction data for occasional audits.
Which solution will meet this requirement in the MOST cost-effective way?

A. Store the data in Amazon Glacier Instant Retrieval. Use Amazon Athena to query the data.
B. Store the data in Amazon S3. Use Amazon Athena to query the data.
C. Store the data in Amazon Glacier Flexible Retrieval. Use Amazon S3 Glacier Select to query the data.
D. Store the data in Amazon S3. Use Amazon S3 Select to query the data.

Answer: C

NEW QUESTION # 79
A company receives marketing campaign data from a vendor. The company ingests the data into an Amazon S3 bucket every 40 to 60 minutes. The data is in CSV format. File sizes are between
100 KB and 300 KB.
A data engineer needs to set-up an extract, transform, and load (ETL) pipeline to upload the content of each file to Amazon Redshift.
Which solution will meet these requirements with the LEAST operational overhead?

A. Creates an AWS Database Migration Service (AWS DMS) task. Specify an appropriate data schema to migrate. Specify the appropriate type of migration to use.
B. Use Amazon Redshift Spectrum to query the S3 bucket. Configure an AWS Glue Crawler for the S3 bucket to update metadata in an AWS Glue Data Catalog.
C. Create an AWS Lambda function that connects to Amazon Redshift and runs a COPY command.
Use Amazon EventBridge to invoke the Lambda function based on an Amazon S3 upload trigger.
D. Create an Amazon Data Firehose stream. Configure the stream to use an AWS Lambda function as a source to pull data from the S3 bucket. Set Amazon Redshift as the destination.

Answer: C

Explanation:
Configuring your S3 bucket to emit "Object Created" events into EventBridge and using a rule to invoke a lightweight Lambda function lets you automatically run a Redshift COPY for each new CSV. This serverless, event-driven pattern requires no continuously running infrastructure and has minimal operational overhead.

NEW QUESTION # 80
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