High-quality DEA-C01 - SnowPro Advanced: Data Engineer Certification Exam Study Group

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Snowflake DEA-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	SnowPro Advanced: Data Engineer Certification Exam
Exam Number:	DEA-C01
Passing Score:	~70% (exact passing score not publicly disclosed by Snowflake)
Exam Format:	Multiple Select, Multiple Choice
Real Exam Qty:	approximately 50 questions
Available Languages:	English
Related Certifications:	SnowPro Core Certification (Recommended Prerequisite)
Exam Price:	$375 USD
Exam Duration:	90 minutes
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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It has similar specifications to the Snowflake DEA-C01 desktop-based practice exam software, but it requires an internet connection. Our Snowflake DEA-C01 practice exam highlights mistakes at the end of each attempt, allowing you to overcome them before it's too late. This kind of approach is great for complete and flawless Snowflake DEA-C01 Test Preparation.

Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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	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	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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q121-Q126):

NEW QUESTION # 121
A data engineer uses AWS Lake Formation to manage access to data that is stored in an Amazon S3 bucket. The data engineer configures an AWS Glue crawler to discover data at a specific file location in the bucket, s3://examplepath. The crawler execution fails with the following error: "The S3 location: s3://examplepath is not registered." The data engineer needs to resolve the error.
Which solution will meet this requirement?

A. Attach an appropriate IAM policy to the IAM role of the AWS Glue crawler to grant the crawler permission to read the S3 location.
B. Configure the S3 bucket policy to allow cross-account access.
C. Create a new AWS Glue database. Assign the correct permissions to the database for the crawler.
D. Register the S3 location in Lake Formation to allow the crawler to access the data.

Answer: D

Explanation:
In Lake Formation, you must explicitly register each S3 path as a data location before any Glue crawler or user can access it. Registering s3:// examplepath in Lake Formation grants the crawler the metadata permissions it needs to crawl that location.

NEW QUESTION # 122
Snowflake does not provide which of following set of SQL functions to support retrieving infor-mation about tasks?

A. TASK_HISTORY
B. SYSTEM$CURRENT_USER_TASK_NAME
C. SYSTEM$TASK_DEPENDENTS_ENABLE
D. TASK_QUERY_HISTORY
E. TASK_DEPENDENTS

Answer: E

Explanation:
Explanation
SYSTEM$CURRENT_USER_TASK_NAME
Returns the name of the task currently executing when invoked from the statement or stored proce-dure defined by the task.
SYSTEM$TASK_DEPENDENTS_ENABLE
Recursively resumes all dependent tasks tied to a specified root task.
TASK_DEPENDENTS
This table function returns the list of child tasks for a given root task in a DAG of tasks.
TASK_HISTORY
This table function can be used to query the history of task usage within a specified date range.

NEW QUESTION # 123
As Data Engineer, you have been asked to access data held in AWS Glacier Deep Archive storage class for Historical Data Analysis, which one is the correct statement to recommend?

A. Upload (i.e. stage) files to your cloud storage account using the tools provided by the cloud storage service.
B. Loading data from AWS cloud storage services is supported regardless of the cloud platform that hosts your Snowflake account.
C. Data can be accessed from External stage using AWS Private link in this case.
D. You cannot access data held in archival cloud storage classes that requires restoration before it can be retrieved.
E. We can simply access AWS Glacier Deep Archive storage External Stage data using PUT command.

Answer: D

Explanation:
Explanation
External stage
References data files stored in a location outside of Snowflake. Currently, the following cloud stor-age services are supported:
Amazon S3 buckets
Google Cloud Storage buckets
Microsoft Azure containers
The storage location can be either private/protected or public.
You cannot access data held in archival cloud storage classes that requires restoration before it can be retrieved. These archival storage classes include, for example, the Amazon S3 Glacier Flexible Retrieval or Glacier Deep Archive storage class, or Microsoft Azure Archive Storage.

NEW QUESTION # 124
A data engineer needs to use an Amazon QuickSight dashboard that is based on Amazon Athena queries on data that is stored in an Amazon S3 bucket. When the data engineer connects to the QuickSight dashboard, the data engineer receives an error message that indicates insufficient permissions.
Which factors could cause to the permissions-related errors? (Choose two.)

A. The Athena tables are not cataloged.
B. QuickSight does not have access to decrypt S3 data.
C. There is no IAM role assigned to QuickSight.
D. QuickSight does not have access to the S3 bucket.
E. There is no connection between QuickSight and Athena.

Answer: B,D

NEW QUESTION # 125
A company saves customer data to an Amazon S3 bucket. The company uses server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the bucket. The dataset includes personally identifiable information (PII) such as social security numbers and account details.
Data that is tagged as PII must be masked before the company uses customer data for analysis.
Some users must have secure access to the PII data during the pre-processing phase. The company needs a low-maintenance solution to mask and secure the PII data throughout the entire engineering pipeline.
Which combination of solutions will meet these requirements? (Choose two.)

A. Write custom scripts in an application to mask the PII data and to control access.
B. Use Amazon GuardDuty to monitor access patterns for the PII data that is used in the engineering pipeline.
C. Configure an Amazon Macie discovery job for the S3 bucket.
D. Use AWS Identity and Access Management (IAM) to manage permissions and to control access to the PII data.
E. Use AWS Glue DataBrew to perform extract, transform, and load (ETL) tasks that mask the PII data before analysis.

Answer: D,E

Explanation:
AWS Glue DataBrew is a data preparation service that simplifies the process of cleaning and normalizing data, including masking PII data. It allows you to visually transform data and apply masking rules before the data is used for analysis. This solution is low-maintenance and seamlessly integrates with S3 for processing data.
AWS Identity and Access Management (IAM) can be used to manage permissions and control access to the PII data. IAM provides the necessary fine- grained access control for determining which users or roles can view or modify the PII data during the pre-processing and analysis phases.
GuardDuty is primarily a threat detection service. While it can monitor unusual access patterns, it does not provide the necessary tools for masking or securing PII data during the engineering pipeline.
Amazon Macie is useful for discovering and classifying PII in S3 buckets, but it does not handle the actual masking or securing of PII data. It is more for classification and monitoring rather than processing or access control.
Custom scripts can be error-prone, labor-intensive, and require ongoing maintenance. This approach introduces unnecessary complexity compared to the managed solution offered by AWS Glue DataBrew.

NEW QUESTION # 126
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