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Snowflake DEA-C01 Exam Overview:

Certification Vendor:Snowflake
Exam Name:SnowPro Advanced: Data Engineer Certification Exam
Exam Number:DEA-C01
Exam Price:$375 USD
Passing Score:750 / 1000
Real Exam Qty:65
Related Certifications:SnowPro Advanced: Architect
SnowPro Advanced: Administrator
SnowPro Advanced: Data Analyst
SnowPro Advanced: Security Engineer
SnowPro Core
SnowPro Advanced: Data Scientist
Certificate Validity Period:2 years
Available Languages:English, Japanese
Exam Duration:115 minutes
Exam Format:Multiple choice, Multiple select
Recommended Training:SnowPro Advanced: Data Engineer Exam Study Guide
Snowflake University Training Courses
Exam Registration:Pearson VUE Registration
Snowflake Certification Portal
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:

TopicDetails
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
  • 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 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 (Q34-Q39):

NEW QUESTION # 34
Which of the following best describes the type of data found in traditional relational databases?

Answer: A


NEW QUESTION # 35
A data engineer needs to analyze time-sensitive sales data. The company stores the data in an Amazon S3 bucket. The data engineer uses AWS Glue Data Catalog to access the data.
When the data engineer performs the analysis, the data engineer notices that some records are missing or out of date.
What is the likely cause of these issues?

Answer: A

Explanation:
Missing or outdated records typically occur when the AWS Glue Data Catalog has not been updated to reflect the latest partitions in the Amazon S3 bucket. The catalog must be crawled or updated so queries and analyses can see the most recent data.


NEW QUESTION # 36
A company has an Amazon Redshift data warehouse that users access by using a variety of IAM roles. More than 100 users access the data warehouse every day.
The company wants to control user access to the objects based on each user's job role, permissions, and how sensitive the data is.
Which solution will meet these requirements?

Answer: B

Explanation:
Role-based access control (RBAC) in Amazon Redshift enables administrators to define roles based on job functions and then assign these roles to users. RBAC allows for granular permissions management based on job roles, aligning well with the need to control access according to each user's role, permissions, and the sensitivity of data. This approach simplifies managing access for a large number of users by using predefined roles instead of individual permissions.


NEW QUESTION # 37
A company has AWS resources in multiple AWS Regions. The company has an Amazon EFS file system in each Region where the company operates. The company's data science team operates within only a single Region. The data that the data science team works with must remain within the team's Region.
A data engineer needs to create a single dataset by processing files that are in each of the company's Regional EFS file systems. The data engineer wants to use an AWS Step Functions state machine to orchestrate AWS Lambda functions to process the data.
Which solution will meet these requirements with the LEAST effort?

Answer: A

Explanation:
AWS DataSync is designed for transferring data between AWS storage services across regions, such as EFS, S3, and other storage systems. By using DataSync, you can efficiently transfer data from each of the Regional EFS file systems to the EFS file system in the data science team's Region.
This allows the data to remain within the data science team's Region while being processed, which meets the requirement that data cannot leave the Region.
Once the data is transferred, Lambda functions in the same Region as the data science team can mount the local EFS file system and process the data, minimizing complexity and the risk of network-related latency or failures from cross-region data processing.
This approach ensures minimal operational effort because DataSync automates the transfer process and works seamlessly with EFS, while keeping the data localized for processing by Lambda functions in the same Region.


NEW QUESTION # 38
A company stores objects in an Amazon S3 bucket. The company crawls the objects so that Amazon Athena can query the data.
A data engineer manually moved all objects from the partition with a path prefix of status=01 to the prefix status=02. The status=01 partition location is now empty. However, the status=01 partition location still appears in the AWS Glue Data Catalog metadata.
Which Athena command should the data engineer run to resolve the metadata discrepancy?

Answer: C

Explanation:
When data is manually moved and a partition location becomes empty, the AWS Glue Data Catalog still retains the old partition metadata. To resolve this discrepancy, the partition must be explicitly removed from the table metadata. The appropriate command deletes the outdated partition entry so that Athena reflects the current data layout.


NEW QUESTION # 39
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