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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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 (Q82-Q87):

NEW QUESTION # 82
A company extracts approximately 1 TB of data every day from data sources such as SAP HANA, Microsoft SQL Server, MongoDB, Apache Kafka, and Amazon DynamoDB. Some of the data sources have undefined data schemas or data schemas that change.
A data engineer must implement a solution that can detect the schema for these data sources.
The solution must extract, transform, and load the data to an Amazon S3 bucket. The company has a service level agreement (SLA) to load the data into the S3 bucket within 15 minutes of data creation.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use AWS Glue to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.
B. Use Amazon EMR to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.
C. Create a PySpark program in AWS Lambda to extract, transform, and load the data into the S3 bucket.
D. Create a stored procedure in Amazon Redshift to detect the schema and to extract, transform, and load the data into a Redshift Spectrum table. Access the table from Amazon S3.

Answer: A

NEW QUESTION # 83
A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.
Which Step Functions state should the data engineer use to meet these requirements?

A. Map state
B. Choice state
C. Parallel state
D. Wait state

Answer: A

Explanation:
Map state is designed precisely for the requirement described. It allows you to iterate over a collection of items, processing each item individually. The Map state can automatically manage the iteration and execute the specified transformation on each item in parallel, making it the perfect choice for parallel processing of a large collection of data files.

NEW QUESTION # 84
A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.
The data engineer requires a less manual way to update the Lambda functions.
Which solution will meet this requirement?

A. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.
B. Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket.
C. Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.
D. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.

Answer: A

Explanation:
After you create a layer, you can apply it to any number of functions in your account. Without layers, you need to include the same dependencies in each individual deployment package.
https://docs.aws.amazon.com/lambda/latest/dg/chapter-layers.html

NEW QUESTION # 85
A data engineer needs to build an extract, transform, and load (ETL) job. The ETL job will process daily incoming .csv files that users upload to an Amazon S3 bucket. The size of each S3 object is less than 100 MB.
Which solution will meet these requirements MOST cost-effectively?

A. Write a PySpark ETL script. Host the script on an Amazon EMR cluster.
B. Write a custom Python application. Host the application on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster.
C. Write an AWS Glue Python shell job. Use pandas to transform the data.
D. Write an AWS Glue PySpark job. Use Apache Spark to transform the data.

Answer: D

Explanation:
AWS Glue Python Shell Job is billed $0.44 per DPU-Hour for each job.
AWS Glue PySpark is billed $0.29 per DPU-Hour for each job with flexible execution and $0.44 per DPU-Hour for each job with standard execution.
https://aws.amazon.com/glue/pricing/

NEW QUESTION # 86
In data modeling, an entity-relationship diagram (ERD) is primarily used to:

A. Illustrate relationships between entities.
B. Cleanse dirty data.
C. Transform raw data into structured data.
D. Store data in a physical location.

Answer: A

NEW QUESTION # 87
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Avail Newest DEA-C01 Latest Braindumps Pdf to Pass DEA-C01 on the First Attempt

Free PDF 2025 DEA-C01: SnowPro Advanced: Data Engineer Certification Exam Newest Latest Braindumps Pdf

Snowflake DEA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q82-Q87):

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