Free Amazon AWS-DEA-C01 Exam Questions

Question 1

A data engineer needs to build an enterprise data catalog based on the company's Amazon S3 buckets andAmazon RDS databases. The data catalog must include storage format metadata for the data in the catalog.Which solution will meet these requirements with the LEAST effort?

A : Use an AWS Glue crawler to scan the S3 buckets and RDS databases and build a data catalog. Use data stewards to inspect the data and update the data catalog with the data format.

B : Use an AWS Glue crawler to build a data catalog. Use AWS Glue crawler classifiers to recognize the format of data and store the format in the catalog.

C : Use Amazon Macie to build a data catalog and to identify sensitive data elements. Collect the data format information from Macie.

D : Use scripts to scan data elements and to assign data classifications based on the format of the data.

Answer: B

Question 2

A healthcare organization stores patient records from multiple regions in an Amazon S3 bucket, which is used for regional health analysis. A data compliance team needs to ensure that health analysts can only access patient records from their specific region to comply with local privacy regulations.

Which solution will enable this requirement with the minimum amount of operational effort?

A : Import the data into an Amazon Aurora database, set up regional schemas, and create IAM policies that grant access to these schemas based on the analyst's region.

B : Implement AWS Lake Formation, register the S3 bucket as a data lake, and utilize Lake Formation's fine-grained access control to manage region-specific data access.

C : Distribute the data across multiple AWS Regions correlating to the patient locations, and implement IAM policies to grant data access to analysts within the same geographical region.

D : Segment the patient records into different S3 prefixes per region, and use IAM bucket policies to restrict access to analysts based on their regional assignment.

Answer: B

Question 3

As a Data Engineer, you've been given the task of enhancing the performance of a business analytics application. This application predominantly performs complex, read-intensive queries against large, historical datasets.

The data is currently housed in a MySQL database on Amazon RDS. However, due to the increasing dataset size and query complexity, query performance has significantly degraded. To address this issue, you are considering implementing Amazon ElastiCache.

Which caching strategy would be most effective in this scenario to improve query performance?

A : Use ElastiCache for Memcached implementing an Invalidation strategy, where cache entries are invalidated or updated whenever the database write operations occur.

B : Implement ElastiCache for Redis using a Lazy-Loading strategy, loading data into the cache only when it is requested.

C : Utilize ElastiCache for Memcached with a Write-Through caching strategy, ensuring data is written to both the cache and the database simultaneously.

D : Deploy ElastiCache for Redis with a Write-Around caching strategy, where data is written directly to the database and only the data read from the database is cached.

Answer: B

Question 4

A photography studio stores its high-resolution image files in an Amazon S3 bucket. Recently, they encountered issues with accidental overwrites of important files. The studio requires a solution to prevent the overwriting and accidental deletion of their images while ensuring that the latest version of a file is readily accessible.

Which single feature should the photography studio enable on their S3 bucket to address this issue effectively?

A : Activate S3 Versioning to maintain multiple versions of each file.

B : Enable S3 Object Lock in compliance mode for strict WORM (Write Once, Read Many) protection.

C : Configure S3 Intelligent-Tiering to manage the storage of the files efficiently.

D : Implement S3 Lifecycle policies to archive older versions of files to S3 Glacier.

Answer: A

Question 5

A research institution is looking to transition their on-premises data analytics platform, which includes Apache Hadoop clusters and a comprehensive data catalog managed in an Apache Hive metastore, to the AWS cloud. They are adopting Amazon EMR for their Hadoop workloads and require a serverless, cost-effective solution to migrate and manage their existing data catalog.

Which solution should the institution implement to migrate their Hive metastore to AWS while ensuring a serverless and cost-effective data catalog management?

A : Migrate the Hive metastore to Amazon RDS with AWS Database Migration Service (DMS), then connect the RDS instance to Amazon EMR clusters.

B : Use AWS Glue Data Catalog to import the existing Hive metastore, making it the centralized metadata repository, and integrate it with Amazon EMR.

C : Set up an Amazon EMR cluster with a configured Hive metastore, migrate the on-premises metastore to EMR, and utilize AWS Glue Data Catalog for catalog synchronization.

D : Implement Amazon Athena to reconstruct the data catalog from the Hive metastore data stored in Amazon S3, integrating it with EMR for analytics.

Answer: B