Free AWS Certified Data Engineer  (DEA-C01) Practice Test 4

The company needs to manage these jobs efficiently on AWS, ensuring optimal resource utilization and cost-effectiveness. They also require the ability to schedule jobs, manage dependencies, and handle job retries automatically.
What is the most suitable AWS solution to meet these requirements?

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Which of the following deployment strategies should the team choose to maximize container usage performance and control?

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What is the most efficient way to enable the Lambda function to access and process these large files?

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The team is deciding on the most appropriate data structure or AWS service to use for this task to ensure both performance efficiency and query optimization. Which of the following should they consider?

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The method must utilize automatic triggering mechanisms for immediate response to data uploads and robust access control measures for data security.
Which of the following options best achieves this objective?

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Which of the following approaches should the consultant consider first to diagnose and address the performance issue?

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The team seeks to maintain high performance during peak loads without over-provisioning resources during off-peak times. They also need to ensure seamless integration with Kubernetes ecosystem tools.
Which approach should they consider for container deployment and management to optimize performance while controlling costs?

Select 1 option(s):

Which of the following would be the best approach to configure the Lambda functions to meet the concurrency and performance needs while optimizing costs?

Select 1 option(s):

They require a CI/CD solution that not only automates build and test processes upon each commit but also allows for customizable, condition-based deployment strategies (e.g., deploying only specific branches or tags, or based on commit messages).
Given these requirements, which AWS service or combination of services would be the most effective?

Select 1 option(s):

Which actions should the Data Engineer take to identify and rectify the scaling issues and prevent future timeouts and load failures? (Select TWO)

Select 2 option(s):

Given the need to reduce costs without impacting the performance of the ETL workload significantly, what should the engineer consider implementing?

Select 1 option(s):

Which of the following approaches would be most effective in this scenario?

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To ensure their changes do not affect the stable version of the application during development, which Git command should they use initially to safely begin working on the new feature in their AWS CodeCommit repository?

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Client‘s Question: “We are setting up an AWS Glue ETL job for our streaming data. Can you explain how the AWS Glue Schema Registry plays a role in this setup and ensures our data integrity?”

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Which of the following points would you emphasize as a key difference in the AWS Glue implementation of Spark?

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The solution must ensure minimal latency, maintain data integrity, and support the rapid scaling needs of the startup.
What approach should the Cloud Data Engineer take to establish efficient and reliable data replication between Amazon Aurora and Amazon Redshift?

Select 1 option(s):

Which Redshift feature should the company use to meet this requirement?

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The team has noticed that new partitions are not automatically available in Athena queries, requiring manual intervention to run MSCK REPAIR TABLE commands periodically. They want to streamline this process for better efficiency and reliability.
What is the most appropriate strategy to automatically synchronize the new partitions with the Glue data catalog?

Select 1 option(s):

What approach should the team take to effectively manage the lifecycle of data in S3 and DynamoDB while adhering to cost and compliance requirements?

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Which of the following strategies should they employ?

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What would be the easiest way, using AWS services, to convert the Oracle database schema to be compatible with Aurora PostgreSQL and to perform the subsequent data migration?

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How can the team effectively establish and maintain data lineage for this project using AWS tools?

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Given the evolving nature of the data and the models, it‘s vital for the team to have a thorough understanding of the model development history, including data sources, feature transformations, and model parameter changes. This understanding is crucial not only for model tuning but also for compliance with industry regulations.
What AWS service should the team use to best track and manage the data lineage for their machine learning workflows in this scenario?

Select 1 option(s):

The data is highly dynamic, with frequent reads and writes. The API must offer low latency and high availability, and be capable of scaling automatically to handle peak loads during business hours.
Given these requirements, which architecture should the team implement?

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Your primary objective is to efficiently transfer this data from the RDS database to a data lake in AWS, ensuring reliable storage and preparing the dataset for analytical processing with minimal yet capable transformation steps due to its complexity.
Which combination of AWS services would be most appropriate?

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What is the most efficient and cost-effective architecture to expose this data via an API?

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Which bucket structure and naming strategy should the team implement for effective management and processing of the data at different stages of the ETL pipeline?

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Which combination of actions should the Cloud Data Engineering Team take to implement IaC for serverless deployments of data ingestion and transformation pipelines? (Select THREE)

Select 3 option(s):

Considering the need for efficient processing and the requirement to support regular and complex queries in Redshift, which combination of AWS services and steps would be most suitable?

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Which approach would be most effective and secure for accomplishing this task?

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Which of the following steps should the team take to effectively troubleshoot and enhance the ETL process? (Select THREE)

Select 3 option(s):

Considering the need for high availability, scalability, and near real-time processing, which of the following AWS service combinations is the most appropriate for handling these specific transaction types?

Select 1 option(s):

Which of the following steps should you take first to resolve this issue?

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Given that their infrastructure includes Amazon EMR clusters, Amazon S3 buckets for data storage, and AWS Lambda functions for data processing tasks, which IaC service and strategy would be the most effective to meet their needs?

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Which of the following options would most effectively enhance the Glue job‘s performance?

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Which of the following approaches should they adopt to effectively manage and automate the deployment of their serverless data pipeline across different environments using AWS SAM?

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However, they are experiencing increased latency during peak data bursts. Wanting to make minimal adjustments to their current setup and maintain cost-efficiency, which configuration change would be the most effective for addressing this latency issue?

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Which feature of Glue DataBrew would be most beneficial for automatically detecting and addressing data quality issues such as missing values and inconsistencies?

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Which of the following approaches is most appropriate for establishing these connections?

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