View Full Amazon AWS Certified Data Engineer – Associate DEA-C01 Exam Dumps and Practice Test Dumps.

 

Question 181

A data engineer needs to identify the number of records in each category in a dataset. Which SQL function should be used with GROUP BY?

1. COUNT()
2. LOWER()
3. SUBSTRING()
4. COALESCE()

Correct Answer: 1

Explanation:

The SQL COUNT() aggregate function is used to count rows or non-NULL values. When combined with GROUP BY, it can calculate the number of records belonging to each category. For example, SELECT category, COUNT(*) FROM products GROUP BY category returns the number of products in each category. LOWER() converts text to lowercase, SUBSTRING() extracts part of a string, and COALESCE() returns the first non-NULL value from its arguments. Therefore, COUNT() is the appropriate function when a data engineer needs to calculate record counts for each group in a dataset.

Question 182

A company wants to ensure that an ETL process does not lose records when a transformation fails. What should the data engineer implement?

1. Delete failed records
2. Ignore transformation errors
3. Store failed records in a quarantine location
4. Disable logging

Correct Answer: 3

Explanation:

A quarantine location provides a safe place to store records that fail validation or transformation instead of deleting them. The main ETL pipeline can continue processing valid records while problematic records are preserved for investigation and possible reprocessing. This approach improves data reliability and prevents accidental data loss. The data engineer can later determine why a record failed, correct the problem, and process it again. Deleting failed records permanently makes recovery difficult, while ignoring errors can introduce incomplete or incorrect data into downstream systems. Therefore, storing failed records in a quarantine location is an effective data engineering practice.

Question 183

A data engineer wants to encrypt objects in Amazon S3 using AWS Key Management Service keys. Which S3 encryption option should be used?

1. SSE-S3
2. SSE-KMS
3. TLS
4. Client-side compression

Correct Answer: 2

Explanation:

SSE-KMS, or server-side encryption with AWS KMS keys, allows Amazon S3 objects to be encrypted using keys managed through AWS Key Management Service. It provides additional control over key policies, permissions, and auditing compared with standard S3-managed encryption. Data engineers can use customer-managed KMS keys when more control over key management is required. SSE-S3 uses keys managed by Amazon S3, while TLS protects data in transit rather than serving as S3 object encryption at rest. Compression only reduces data size. Therefore, SSE-KMS is the correct option when S3 objects need to be encrypted using AWS KMS.

Question 184

A company needs a serverless service that can transform and prepare data from multiple sources before loading it into analytical storage. Which AWS service is most appropriate?

1. Amazon Route 53
2. Amazon CloudFront
3. AWS Glue
4. Amazon EBS

Correct Answer: 3

Explanation:

AWS Glue is a serverless data integration and ETL service designed to discover, transform, prepare, and move data between supported sources and destinations. Glue jobs can process data from Amazon S3, databases, and other sources and transform it into formats suitable for analytics. Glue also integrates with the Glue Data Catalog for managing metadata. Route 53 provides DNS, CloudFront provides content delivery, and EBS provides block storage for compute instances. Therefore, AWS Glue is the most appropriate service when a company needs serverless data transformation and preparation as part of an analytical data pipeline.

Question 185

A data engineer needs to find rows where a numeric column contains values greater than 100. Which SQL clause should be used to filter the rows?

1. GROUP BY
2. ORDER BY
3. WHERE
4. UNION

Correct Answer: 3

Explanation:

The SQL WHERE clause filters rows based on a specified condition. For example, WHERE amount > 100 returns only rows where the value in the amount column is greater than 100. Filtering early in a query can also reduce the amount of data that needs to be processed, depending on the query engine and data architecture. GROUP BY is used to create groups for aggregation, ORDER BY sorts query results, and UNION combines results from multiple compatible queries. Therefore, the WHERE clause is the correct choice for filtering records based on a numeric condition.

Question 186

A company wants to continuously capture changes made to a source relational database and replicate those changes to an AWS target database. Which AWS DMS capability should be used?

1. Change Data Capture (CDC)
2. S3 Lifecycle
3. Glue Crawler
4. Athena Workgroup

Correct Answer: 1

Explanation:

AWS Database Migration Service supports Change Data Capture (CDC), which captures ongoing changes made to a source database after the initial migration. CDC can replicate inserts, updates, and deletes to a target system, helping keep the target synchronized with the source. This capability is useful when organizations need to minimize downtime during database migrations or continuously replicate operational data for analytics. S3 Lifecycle manages object transitions and expiration, Glue Crawlers discover data metadata, and Athena workgroups organize query workloads. Therefore, AWS DMS Change Data Capture is the appropriate capability for continuously replicating database changes.

Question 187

A data engineer wants to automatically discover tables and schemas from files stored in Amazon S3. Which AWS Glue component should be used?

1. Glue Studio
2. Glue Crawler
3. Glue Connection
4. Glue DataBrew

Correct Answer: 2

Explanation:

AWS Glue Crawlers automatically inspect supported data sources and infer information such as schemas, file formats, and partitions. When a crawler scans data stored in Amazon S3, it can create or update table metadata in the AWS Glue Data Catalog. This allows services such as Athena and Glue jobs to understand how the data is structured. Glue Studio provides a visual interface for building ETL jobs, connections provide connectivity information, and DataBrew is focused on visual data preparation. Therefore, a Glue Crawler is the appropriate component for automatically discovering schemas and creating metadata for S3 datasets.

Question 188

A company wants to query only the columns required for an analytical report from a large Parquet dataset. Which feature helps reduce unnecessary data scanning?

1. Column pruning
2. Object Lock
3. Versioning
4. Replication

Correct Answer: 1

Explanation:

Column pruning allows a query engine to read only the columns required by a query instead of scanning every column in a dataset. This is especially beneficial with columnar formats such as Apache Parquet, where individual columns can be accessed efficiently. For example, if a report requires only customer ID and revenue, the query engine can avoid reading unrelated columns. Object Lock protects objects from deletion or overwriting, Versioning preserves previous object versions, and replication creates copies of data. Therefore, column pruning is the appropriate optimization for reducing unnecessary data scanning when querying large Parquet datasets.

Question 189

A data engineer wants to securely share a specific S3 dataset with different teams while maintaining centralized access controls. Which AWS service provides fine-grained data lake permissions?

1. Amazon SQS
2. AWS Lake Formation
3. Amazon CloudFront
4. Amazon EBS

Correct Answer: 2

Explanation:

AWS Lake Formation provides centralized governance and fine-grained permissions for data lakes. It can control access to databases, tables, columns, and other data resources while integrating with services such as the AWS Glue Data Catalog and Amazon Athena. This allows organizations to share data with different teams while maintaining consistent access policies. SQS is a messaging service, CloudFront distributes content, and EBS provides block storage. Therefore, Lake Formation is the best choice when a company needs to securely share S3-based datasets while maintaining centralized and granular data access controls.

Question 190

A data engineer needs to sort query results by transaction date from newest to oldest. Which SQL clause should be used?

1. DISTINCT
2. GROUP BY
3. WHERE
4. ORDER BY

Correct Answer: 4

Explanation:

The SQL ORDER BY clause sorts query results according to one or more columns. To sort transaction dates from newest to oldest, a query can use ORDER BY transaction_date DESC. The DESC keyword specifies descending order, while ASC specifies ascending order. DISTINCT removes duplicate results, GROUP BY groups rows for aggregation, and WHERE filters records according to conditions. Therefore, ORDER BY is the correct SQL clause for sorting transaction records by date from the most recent to the oldest.

Question 191

A company wants to run a data processing job automatically whenever a new file is uploaded to an S3 bucket. Which architecture is most appropriate?

1. S3 event → Lambda → processing workflow
2. S3 → Route 53 → processing
3. S3 → CloudFront → processing
4. S3 → EBS → processing

Correct Answer: 1

Explanation:

An event-driven architecture can use an Amazon S3 object-created event to trigger AWS Lambda or another supported processing workflow. When a new file arrives, the event can initiate processing automatically without requiring a continuously running server or a manually scheduled job. Lambda can validate or transform the file and can also start services such as Step Functions or Glue depending on the workload. Route 53, CloudFront, and EBS do not provide the appropriate event-driven data processing pattern. Therefore, using an S3 event to trigger Lambda or a downstream workflow is an effective architecture for automatically processing newly uploaded files.

Question 192

A data engineer wants to limit the number of rows returned by a SQL query to the first 100 records. Which SQL clause can be used?

1. LIMIT
2. JOIN
3. HAVING
4. UNION

Correct Answer: 1

Explanation:

The SQL LIMIT clause restricts the number of rows returned by a query in database engines that support it. For example, LIMIT 100 returns up to 100 rows from the query result. It is commonly used during testing, exploration, and situations where only a subset of results is required. JOIN combines rows from multiple tables, HAVING filters grouped results, and UNION combines the results of compatible queries. Therefore, LIMIT is the appropriate clause when a data engineer needs to restrict a query result to the first 100 rows.

Question 193

A company wants to monitor an AWS data pipeline and receive a notification when the number of failed executions exceeds five within a specified period. Which service should be used?

1. AWS KMS
2. Amazon CloudWatch
3. Amazon S3 Glacier
4. AWS Lake Formation

Correct Answer: 2

Explanation:

Amazon CloudWatch provides monitoring capabilities for AWS resources and applications. A data engineer can use CloudWatch metrics to track pipeline failures and configure a CloudWatch Alarm that triggers when the number of failures exceeds a defined threshold. The alarm can then notify an Amazon SNS topic or perform another configured action. KMS manages encryption keys, S3 Glacier provides archival storage, and Lake Formation manages data lake governance. Therefore, Amazon CloudWatch is the appropriate service for monitoring pipeline execution metrics and generating alerts when failure counts exceed an established threshold.

Question 194

A data engineer needs to combine the results of two SQL queries where both queries return the same number and compatible types of columns. Which SQL operator should be used?

1. JOIN
2. UNION
3. WHERE
4. ORDER BY

Correct Answer: 2

Explanation:

The SQL UNION operator combines the result sets of two or more compatible SELECT statements. The queries generally need to return the same number of columns, with corresponding columns having compatible data types. UNION removes duplicate rows from the combined result, while UNION ALL retains duplicates. A JOIN combines columns from related tables based on a join condition, WHERE filters rows, and ORDER BY sorts results. Therefore, UNION is the correct operator when a data engineer needs to combine the results of two compatible SQL queries into a single result set.

Question 195

A company wants to protect S3 objects from accidental deletion while meeting compliance requirements for immutable data. Which feature should be considered?

1. S3 Object Lock
2. S3 Transfer Acceleration
3. S3 Select
4. S3 Inventory

Correct Answer: 1

Explanation:

Amazon S3 Object Lock provides protection against object deletion or overwriting for a configured retention period. It is commonly used for compliance and workloads that require immutable or write-once-read-many (WORM) data. Object Lock can use retention settings and legal holds to control when objects can be modified or deleted. Transfer Acceleration is designed to improve data transfer speeds, S3 Select retrieves subsets of object data, and S3 Inventory provides object metadata reports. Therefore, S3 Object Lock is the appropriate feature when a company needs to protect data from accidental deletion while meeting requirements for immutable storage.

Question 196

A data engineer wants to reduce storage costs for data that has unpredictable access patterns. Which S3 storage class is most appropriate?

1. S3 Standard
2. S3 Intelligent-Tiering
3. S3 Glacier Deep Archive
4. S3 One Zone-IA

Correct Answer: 2

Explanation:

S3 Intelligent-Tiering is designed for data with changing or unpredictable access patterns. It automatically moves objects between access tiers based on how frequently they are accessed, helping reduce storage costs without requiring the data engineer to manually predict future access behavior. S3 Standard is intended for frequently accessed data, while Glacier Deep Archive is optimized for long-term archival with very infrequent access. One Zone-IA is designed for infrequently accessed data stored in a single Availability Zone. Therefore, S3 Intelligent-Tiering is the best option when access patterns are unpredictable and automatic cost optimization is desired.

Question 197

A data engineer needs to retrieve a secret database password from AWS Secrets Manager in an application without storing the password in source code. What is the recommended approach?

1. Hard-code the password in the application
2. Store the password in a public S3 object
3. Retrieve the secret programmatically using Secrets Manager APIs
4. Put the password in a CloudWatch metric

Correct Answer: 3

Explanation:

AWS Secrets Manager allows applications to retrieve sensitive information programmatically at runtime. Instead of placing a database password directly in source code, the application can use an IAM role or other authorized identity to call Secrets Manager and retrieve the required secret. This improves security and makes credential rotation easier. Hard-coding passwords can expose credentials through source repositories, while storing secrets in public S3 objects or CloudWatch metrics is inappropriate and insecure. Therefore, retrieving the secret programmatically from Secrets Manager is the recommended approach for applications and ETL jobs that need secure access to database credentials.

Question 198

A company needs to analyze a very large dataset using distributed Apache Spark processing and wants AWS to manage the underlying cluster infrastructure. Which service should be used?

1. Amazon EMR
2. Amazon Athena
3. Amazon Route 53
4. Amazon SQS

Correct Answer: 1

Explanation:

Amazon EMR is a managed AWS service for running big data frameworks such as Apache Spark, Hadoop, and related technologies. It provides managed cluster infrastructure that can be configured and scaled for large distributed processing workloads. Data engineers can use Spark on EMR for transformations, aggregations, analytics, and other large-scale processing tasks. Athena is primarily a serverless SQL query service for data sources such as S3, Route 53 provides DNS, and SQS provides message queuing. Therefore, Amazon EMR is the most appropriate choice for large-scale distributed Apache Spark processing when managed cluster infrastructure is required.

Question 199

A data engineer wants to ensure that only records meeting predefined quality rules are loaded into a curated data layer. Which process should be implemented?

1. Data validation
2. Data duplication
3. Data deletion
4. Data compression only

Correct Answer: 1

Explanation:

Data validation checks whether incoming records meet predefined quality requirements before they are accepted into a trusted or curated dataset. Validation rules can check fields for correct data types, required values, acceptable ranges, valid formats, and business constraints. Records that fail validation can be sent to a quarantine location for investigation rather than being loaded into the curated layer. Duplication and deletion do not provide systematic quality control, while compression primarily reduces storage and transfer size. Therefore, implementing data validation is the appropriate approach for ensuring that only records meeting defined quality standards enter the curated data layer.

Question 200

A company wants to provide analysts with SQL access to a large data lake stored in Amazon S3 while minimizing infrastructure management. Which service should be used?

1. Amazon EC2
2. Amazon Athena
3. Amazon EBS
4. Amazon ElastiCache

Correct Answer: 2

Explanation:

Amazon Athena provides serverless SQL querying directly against data stored in Amazon S3. Analysts can use SQL to query data lake datasets without provisioning or managing database servers or clusters. Athena can work with various data formats and can use metadata from the AWS Glue Data Catalog to understand table structures and partitions. EC2 requires management of virtual compute resources, EBS provides block storage, and ElastiCache is designed for in-memory caching rather than analytical SQL queries. Therefore, Amazon Athena is the best choice for providing analysts with serverless SQL access to large datasets stored in an S3-based data lake.