AWS Certified Exam (DEA-C01) Practice Test 6

What is the most effective method to accomplish this task, ensuring security and simplicity in accessing AWS services?

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The team has identified that the query performance issues are mainly due to inefficient data scanning and retrieval processes, especially in tables with complex query patterns. They need a solution that specifically optimizes the way data is stored and accessed in these tables to reduce execution times for complex queries.
Which of the following techniques should they implement to improve the query performance on these large tables?

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Which Amazon Redshift feature should they implement?

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Which feature of AWS Glue should they use to simplify and automate the process of data discovery, conversion, and mapping to make the data available for analytics?

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Which approach should they take to streamline and secure the management of access permissions, ensuring that the principle of least privilege is adhered to effectively?

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Which AWS service combination would best fulfill these requirements while ensuring scalability and cost-effectiveness?

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Which combination of AWS services should the data engineering team use for effective monitoring and alerting?

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What approach should the engineer take to optimize container performance for these needs?

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Which strategy should the team adopt to effectively accomplish this task while optimizing performance?

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What change can the consultant recommend to address this performance issue?

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Which combination of AWS features and best practices should the team implement to meet these requirements effectively?

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What approach should the consultant take to ensure more consistent processing performance?

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Which specific feature of Amazon SageMaker ML Lineage Tracking should the team leverage to fulfill this requirement?

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Which of the following would be the most effective recommendation?

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Which combination of AWS storage services and features should the consultant recommend to meet these requirements? (Select TWO)

Select 2 option(s):

The team wants to leverage this data for advanced analytics and machine learning but is facing challenges in consistently cataloging and querying this data efficiently. Additionally, they need to manage frequently evolving schemas as new product attributes and user interaction types are introduced.
How should the team use AWS Glue to address these challenges?

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To optimize query performance while maintaining their relational database structure, which AWS service should the team consider migrating to?

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What data structure and AWS service should they use to optimize these operations?

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What should they prioritize to meet these requirements effectively?

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Which specific CloudFormation feature should they use to meet this requirement most effectively?

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Which approach would best ensure the accuracy and trustworthiness of data by enabling comprehensive data lineage?

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What would be your recommendation?

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What is the most effective method to clean and prepare this dataset, considering the ML context?

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Which of the following approaches to organizing the data lake aligns best with AWS recommendations for handling both sensitive (PII) and non-sensitive data?

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As part of this initiative, you‘ve been tasked to leverage Amazon Macie for enhancing data security. Your goal is to implement a feature of Macie that can continuously monitor and provide alerts for any PII data being stored or processed in an unsecured manner.
Which feature of Amazon Macie should you utilize to continuously monitor Amazon S3 buckets for unsecured Personal Identifiable Information (PII) and provide automated alerts if such data is detected in an insecure state?

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Your team must ensure that backups, snapshots, and replicas for Amazon RDS, Amazon DynamoDB, and Amazon EC2 are confined to these compliant regions, with centralized management and oversight. Which approach is most effective for this requirement?

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What strategy should the team implement to mitigate this issue without compromising data integrity?

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Which schema design would be the most optimal for this scenario?

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Which of the following deployment strategies would best fit these requirements?

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As a Cloud Data Engineering Consultant, which combination of AWS services would you employ to meet these requirements? (Select THREE)

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What sequence of steps should the team follow using AWS services to achieve this migration?

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What Lake Formation feature should be used to efficiently implement this granular security measure?

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Which AWS service and method should the team use to implement an efficient and cost-effective sampling strategy?

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What is the most suitable architecture for this pipeline?

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To optimize the throughput and ensure scalable data distribution without bottlenecks, which approach should you employ, focusing specifically on Amazon Kinesis features?

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What approach should they take to handle schema evolution with AWS Glue for this JSON dataset?

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Which Git command should be used to update the local repository with these latest changes from AWS CodeCommit?

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Which of the following suggestions would be the most effective for maintaining query performance in DynamoDB at scale?

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Which approach would best serve this requirement, considering optimal performance and scalability?

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Which combination of AWS services and features would you recommend to build this data lakehouse architecture?

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Which feature of Amazon MWAA should be utilized to automatically adjust the number of workflow executions in response to the varying workload?

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Which of the following strategies would effectively allow the team to handle the changing characteristics of the S3-stored data? (Select TWO)

Select 2 option(s):

Which of the following benefits is a primary advantage of using Glue DynamicFrames over standard Spark DataFrames in this scenario?

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What approach should the Cloud Data Engineering team adopt to securely configure encryption for access across these AWS account boundaries?

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What is the most effective approach to accomplish this?

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Which of the following would be the most effective and secure way to comply with this security requirement?

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Which two steps are essential to set up this process (Select TWO)

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Which of the following actions should the consultant take to appropriately manage user access and permissions within the Amazon Redshift database? (Select TWO)

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Which of the following actions should the team take to set up encryption across AWS account boundaries correctly? (Select TWO)

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To ensure accurate schema detection and consistent query results in downstream services like Amazon Athena and Amazon Redshift Spectrum, what should the company do?

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The team is looking for a solution that can manage these diverse workflows and specifically requires the ability to write custom operators, scripts, and integrations in a way that is reusable across different workflows. They also require detailed monitoring and logging of each task for debugging and optimization purposes.
Considering these requirements, which AWS service should the team use to orchestrate their data pipeline?

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Which of the following strategies would best help the team improve query performance, considering the nature of their queries and the growing dataset size?

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Given the need for sophisticated querying capabilities and swift retrieval from the existing log repository to manage the large volumes of data efficiently, which AWS service should your team leverage to conduct this analysis effectively?

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Among the following options, which is the most effective solution to ensure efficient and reliable processing within Lambda‘s execution limits?

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What should the engineer include in the SAM template to meet these requirements efficiently?

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Which of the following setups would best meet these requirements?

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Which combination of actions should the Cloud Data Engineering Team take to meet these objectives? (Select TWO)

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What could be the reason for this performance issue, specifically related to the internal workings of Apache Spark within AWS Glue?

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The team needs to determine the most effective schema design strategy to optimize query performance and data management across these services. What should they consider?

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Given the need to facilitate efficient data sharing among different Amazon Redshift clusters without duplicating data, which solution would you recommend to establish a secure and manageable data sharing process?

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