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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
  • 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 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 4
  • 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 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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q223-Q228):

NEW QUESTION # 223
A company is planning to upgrade its Amazon Elastic Block Store (Amazon EBS) General Purpose SSD storage from gp2 to gp3. The company wants to prevent any interruptions in its Amazon EC2 instances that will cause data loss during the migration to the upgraded storage.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: A


NEW QUESTION # 224
A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: D

Explanation:
This solution directly triggers the Lambda function only when a .csv file is uploaded to the S3 bucket, minimizing unnecessary invocations of the Lambda function. It uses a specific event type (s3:ObjectCreated:*) and a filter rule to ensure that the Lambda function is invoked only for relevant events. Additionally, it directly invokes the Lambda function without the need for additional services like Amazon SNS, reducing operational overhead.


NEW QUESTION # 225
A company uses Amazon RDS for MySQL as the database for a critical application. The database workload is mostly writes, with a small number of reads.
A data engineer notices that the CPU utilization of the DB instance is very high. The high CPU utilization is slowing down the application. The data engineer must reduce the CPU utilization of the DB Instance.
Which actions should the data engineer take to meet this requirement? (Choose two.)

Answer: C,D


NEW QUESTION # 226
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: D

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 # 227
A company is designing a serverless data processing workflow in AWS Step Functions that involves multiple steps. The processing workflow ingests data from an external API, transforms the data by using multiple AWS Lambda functions, and loads the transformed data into Amazon DynamoDB.
The company needs the workflow to perform specific steps based on the content of the incoming data.
Which Step Functions state type should the company use to meet this requirement?

Answer: C

Explanation:
The Choice state in AWS Step Functions is designed to enable conditional branching within a workflow. It allows the workflow to evaluate data and make decisions based on specific conditions. This makes it ideal for cases where certain steps in the workflow need to be executed based on the content of the incoming data.


NEW QUESTION # 228
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