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Snowflake DEA-C01 Exam Overview:

Certification Vendor:Snowflake
Exam Name:SnowPro Advanced: Data Engineer Certification Exam
Exam Number:DEA-C01
Certificate Validity Period:2 years
Exam Price:$375 USD
Exam Duration:115 minutes
Passing Score:Not publicly disclosed (Snowflake uses scaled scoring)
Real Exam Qty:Approximately 65 questions
Related Certifications:SnowPro Core Certification
Exam Format:Scenario-based questions, Multiple select, Multiple choice
Available Languages:English
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:

TopicDetails
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
  • 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
  • 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 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
  • 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.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q255-Q260):

NEW QUESTION # 255
How can the following relational data be transformed into semi-structured data using the LEAST amount of operational overhead?

Answer: B

Explanation:
Explanation
This option is the best way to transform relational data into semi-structured data using the least amount of operational overhead. The OBJECT_CONSTRUCT function takes a variable number of key-value pairs as arguments and returns a Snowflake object, which is a variant type that can store JSON data. The function can be used to convert each row of relational data into a JSON object with the column names as keys and the column values as values.


NEW QUESTION # 256
A data engineer needs Amazon Athena queries to finish faster. The data engineer notices that all the files the Athena queries use are currently stored in uncompressed .csv format. The data engineer also notices that users perform most queries by selecting a specific column.
Which solution will MOST speed up the Athena query performance?

Answer: A

Explanation:
Apache Parquet is a columnar storage format optimized for analytical queries. It is highly efficient for query performance, especially when queries involve selecting specific columns, as it allows for column pruning and predicate pushdown optimizations.


NEW QUESTION # 257
A company stores data in Amazon S3 and Amazon RDS. The company needs to apply technical controls to meet security requirements. The company must generate backups of the data and retain the backups for specified retention periods. The company must protect the backups from accidental or malicious deletion during the retention periods.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: C

Explanation:
AWS Backup centrally automates backups for S3 and RDS with scheduled plans and lifecycle policies, and Vault Lock (compliance mode) enforces WORM immutability to prevent modification or deletion during retention, meeting security and retention requirements with minimal administration.


NEW QUESTION # 258
A stock broking firm is working on a new application that stores and updates stock market data in Amazon DynamoDB. Different applications will track these changes in real-time. The team is looking for a tool to capture this changing data, which should be available for processing for up to one year. Streaming data should be cleansed, transformed, and stored in Amazon S3 data lakes.
Which service can be considered?

Answer: A

Explanation:
Amazon DynamoDB offers two streaming models for change data capture,
Kinesis Data Streams for DynamoDB: Data retention with this model is 1 year. It can process stream records using AWS Lambda, Amazon Managed Service for Apache Flink, Kinesis data firehose, or AWS Glue streaming ETL. AWS Glue Streaming ETL can be used to cleanse, and transform streaming data and store it in either Amazon S3 data lakes or JDBC data stores.
DynamoDB Streams: This model retains data for 24 hours. It can process stream records using AWS Lambda and the DynamoDB Streams Kinesis adapter.
Reference:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/streamsmain.html


NEW QUESTION # 259
A lab uses IoT sensors to monitor humidity, temperature, and pressure for a project. The sensors send 100 KB of data every 10 seconds. A downstream process will read the data from an Amazon S3 bucket every 30 seconds.
Which solution will deliver the data to the S3 bucket with the LEAST latency?

Answer: A


NEW QUESTION # 260
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