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

 

Question 161

A data engineer needs to load data from Amazon S3 into Amazon Redshift on a regular basis. Which command can be used to load data from S3 into a Redshift table?

1. COPY
2. INSERTFILE
3. LOADS3
4. IMPORT

Correct Answer: 1

Explanation:

The Amazon Redshift COPY command is designed to load data from external sources such as Amazon S3 into Redshift tables. It can load large amounts of data efficiently and supports various file formats, including CSV, JSON, Avro, Parquet, and others depending on the configuration. The command can also use an IAM role to authorize Redshift to access the S3 location. The other options are not valid Redshift commands for loading S3 data. Therefore, when a data engineer needs to regularly ingest files from Amazon S3 into Amazon Redshift, the COPY command is the appropriate solution.

Question 162

A company wants to prevent an unauthorized user from deleting objects in an S3 bucket while still allowing the user to read those objects. Which principle should the data engineer apply?

1. Data compression
2. Least privilege
3. Partition pruning
4. Data replication

Correct Answer: 2

Explanation:

The principle of least privilege means granting users and applications only the permissions they actually need to perform their tasks. If a user needs to read S3 objects but should not delete them, the user can be granted permissions such as s3:GetObject while excluding deletion permissions such as s3:DeleteObject. This minimizes the potential impact of accidental or malicious actions. Data compression, partition pruning, and replication are unrelated to authorization. Therefore, applying least privilege is the correct security approach because it ensures the user can perform required read operations without receiving unnecessary delete permissions.

Question 163

A data engineer wants to detect when a new object is created in an Amazon S3 bucket and automatically start processing it. Which AWS service can provide event-driven routing for this requirement?

1. Amazon Athena
2. Amazon Redshift
3. Amazon EventBridge
4. AWS KMS

Correct Answer: 3

Explanation:

Amazon EventBridge can receive and route events from AWS services and applications to configured targets. S3 object creation events can be used to initiate downstream processing, such as starting a Lambda function, Step Functions workflow, or other supported target. This enables an event-driven architecture where processing begins when new data arrives instead of relying only on scheduled jobs. Athena is used for querying data, Redshift is a data warehouse, and KMS manages encryption keys. Therefore, Amazon EventBridge is an appropriate service for routing S3-related events and automatically initiating downstream data processing.

Question 164

A company has a large number of small files stored in Amazon S3 and Athena queries are performing poorly. Which action can help improve analytical performance?

1. Convert the files into a more efficient columnar format and compact them
2. Create more IAM users
3. Disable compression
4. Increase the number of S3 prefixes randomly

Correct Answer: 1

Explanation:

Large numbers of small files can create overhead during analytical queries because the query engine must open and process many individual objects. Compaction combines smaller files into fewer larger files, while converting data into a columnar format such as Parquet can improve scanning efficiency through column pruning and compression. Creating additional IAM users does not improve query performance, disabling compression can increase the amount of data scanned, and randomly increasing prefixes does not address the small-file problem. Therefore, compacting small files and converting them to an efficient columnar format is an effective strategy for improving Athena query performance.

Question 165

A data engineer needs to securely provide an AWS Glue job with permission to access Amazon S3 without embedding long-term access keys in the job code. What should be used?

1. IAM role
2. Hard-coded access key
3. Database password
4. S3 object metadata

Correct Answer: 1

Explanation:

An IAM role allows AWS services such as AWS Glue to obtain temporary credentials for accessing other AWS resources. A Glue job can assume an IAM role with the permissions required to read or write specific S3 locations. This avoids embedding long-term access keys directly in application or ETL code, improving security and simplifying credential management. Hard-coded access keys are difficult to manage securely, while database passwords and S3 object metadata do not provide AWS authorization. Therefore, an IAM role with appropriate least-privilege permissions is the recommended approach for allowing a Glue job to access Amazon S3 securely.

Question 166

A data engineer wants to query data stored in Parquet files in Amazon S3 but needs to select only a few columns from a very large dataset. Why is Parquet beneficial?

1. It requires all columns to be read
2. It supports columnar storage and column pruning
3. It converts all data to XML
4. It prevents S3 partitioning

Correct Answer: 2

Explanation:

Parquet is a columnar file format, meaning data is organized and stored by columns rather than as traditional row-oriented records. When a query selects only a few columns, engines such as Athena can read only the required columns instead of scanning every column in the file. This process, known as column pruning, can reduce data scanned and improve query performance. Parquet also provides efficient compression and encoding. The other options are incorrect because Parquet does not require all columns to be read, does not convert data to XML, and does not prevent S3 partitioning. Therefore, columnar storage and column pruning are key benefits of Parquet.

Question 167

A company wants to automatically run an AWS Glue job whenever a previous Glue job finishes successfully. Which AWS Glue capability can be used to define this dependency?

1. Glue Trigger
2. S3 Object Lock
3. CloudTrail Trail
4. KMS Key Policy

Correct Answer: 1

Explanation:

AWS Glue Triggers can start jobs or crawlers based on different conditions, including the completion status of another Glue job. A trigger can be configured so that a downstream job starts after an upstream job completes successfully. This allows data engineers to build dependencies between different ETL tasks and create automated workflows. S3 Object Lock is used for object protection, CloudTrail records API activity, and KMS key policies control access to encryption keys. Therefore, a Glue Trigger is the appropriate feature when one Glue job needs to automatically start after another job completes successfully.

Question 168

A data engineer wants to store query results from Amazon Athena in Amazon S3 for later analysis. What happens to Athena query results by default?

1. They are stored in Amazon S3
2. They are stored in Amazon RDS
3. They are stored in Amazon DynamoDB
4. They are stored only in memory

Correct Answer: 1

Explanation:

Amazon Athena stores query results in an Amazon S3 location configured for the Athena workgroup or query execution settings. This allows query results to be retained and accessed later for analysis or downstream processing. The results can also be reused by other applications or queried again if appropriate. Athena itself is a serverless query service and does not require a traditional database to store query results. Therefore, Amazon S3 is the correct location for Athena query output. Data engineers should also consider appropriate S3 permissions, encryption, lifecycle rules, and retention requirements for these result files.

Question 169

A company wants to monitor AWS API calls made by users and services for security auditing. Which service should be used?

1. AWS CloudTrail
2. Amazon ElastiCache
3. Amazon Athena
4. Amazon S3 Glacier

Correct Answer: 1

Explanation:

AWS CloudTrail records API activity across AWS accounts and services. CloudTrail events can provide information about who performed an action, what API operation was called, which resource was affected, and when the activity occurred. This makes CloudTrail valuable for security auditing, governance, compliance, and investigation of suspicious activity. ElastiCache is an in-memory caching service, Athena is used to query data, and S3 Glacier is intended for archival storage. Therefore, AWS CloudTrail is the correct service for monitoring and auditing AWS API calls made by users, roles, and services.

Question 170

A data engineer needs to store frequently changing application configuration values that should be retrieved securely by an ETL application. Which AWS service is most suitable?

1. Amazon CloudFront
2. AWS Systems Manager Parameter Store
3. Amazon Route 53
4. Amazon EBS

Correct Answer: 2

Explanation:

AWS Systems Manager Parameter Store provides centralized storage for configuration values and parameters used by applications and AWS services. It supports secure parameter types that can be encrypted using AWS KMS, making it useful for storing sensitive configuration information without embedding it directly in application code. Parameters can be retrieved programmatically by authorized applications and updated centrally when configuration changes. CloudFront is a content delivery service, Route 53 provides DNS, and EBS provides block storage. Therefore, Systems Manager Parameter Store is a suitable solution when an ETL application needs secure, centrally managed, and frequently changing configuration values.

Question 171

A data engineer wants to ensure that a Kinesis Data Stream can handle increased traffic when the number of incoming records grows significantly. What should the engineer consider?

1. Increase the stream’s shard capacity
2. Disable encryption
3. Remove partition keys
4. Delete old records immediately

Correct Answer: 1

Explanation:

Kinesis Data Streams uses shards to provide stream capacity for ingesting and processing records. When traffic increases beyond the current capacity, the stream may need additional shard capacity. Resharding or using appropriate capacity modes can help accommodate increased throughput requirements. Partition keys determine how records are distributed across shards and should not simply be removed to solve capacity issues. Encryption does not directly determine stream throughput, and deleting records does not increase the stream’s ingestion capacity. Therefore, the data engineer should evaluate and increase shard capacity when a Kinesis stream needs to handle significantly higher traffic.

Question 172

A company wants to automatically move older S3 objects to a lower-cost storage class after 90 days. Which feature should be configured?

1. S3 Object Lock
2. S3 Lifecycle rule
3. AWS CloudTrail
4. Amazon Macie

Correct Answer: 2

Explanation:

Amazon S3 Lifecycle rules allow organizations to automatically transition objects between storage classes based on conditions such as object age. A lifecycle rule can be configured to move objects to a lower-cost storage class after 90 days, helping optimize storage costs while maintaining access to the data. Lifecycle rules can also expire objects when they are no longer needed. Object Lock is designed to protect objects from deletion or overwriting, CloudTrail records API activity, and Macie identifies sensitive information in S3. Therefore, an S3 Lifecycle rule is the appropriate solution for automatically transitioning older objects to a lower-cost storage class.

Question 173

A data engineer wants to create a centralized metadata repository that can be accessed by Athena, Glue, and other analytics services. Which component should be used?

1. AWS Glue Data Catalog
2. Amazon CloudFront
3. Amazon SQS
4. AWS Lambda Layer

Correct Answer: 1

Explanation:

The AWS Glue Data Catalog acts as a centralized metadata repository for data assets. It can store information such as table definitions, schemas, locations, partitions, and file formats. Services such as Amazon Athena can use the catalog to understand datasets stored in Amazon S3 and query them using SQL. Glue ETL jobs and other analytics services can also use catalog metadata as part of data processing workflows. CloudFront is a content delivery service, SQS is a message queue, and Lambda Layers package reusable code. Therefore, the Glue Data Catalog is the appropriate component for centralized data metadata management.

Question 174

A data engineer wants to protect a data pipeline from temporary network failures when calling an AWS service. Which approach is generally recommended?

1. Retry with exponential backoff
2. Retry continuously without delays
3. Disable error handling
4. Immediately delete the failed data

Correct Answer: 1

Explanation:

Temporary network failures and service throttling can occur in distributed applications. Retry logic with exponential backoff allows the application to retry failed operations after progressively increasing delays. This reduces the chance of overwhelming a service with repeated requests and gives temporary conditions time to recover. Retry attempts should generally have a maximum limit and may include jitter to reduce synchronized retries. Continuously retrying without delays can increase load and make failures worse. Disabling error handling or deleting failed data can result in unreliable processing or data loss. Therefore, exponential backoff is a recommended technique for handling transient failures.

Question 175

A company wants to analyze application logs stored in Amazon CloudWatch Logs using a query language and identify errors occurring during a specific time period. Which feature should be used?

1. CloudWatch Logs Insights
2. Amazon Macie
3. AWS Lake Formation
4. Amazon S3 Glacier

Correct Answer: 1

Explanation:

CloudWatch Logs Insights provides an interactive query capability for analyzing log data stored in CloudWatch Logs. Data engineers can use its query language to filter, aggregate, sort, and analyze log events, making it useful for troubleshooting applications and data pipelines. For example, an engineer can search for error messages during a particular time window and determine how frequently they occur. Macie is focused on sensitive-data discovery, Lake Formation manages data lake governance, and S3 Glacier provides archival storage. Therefore, CloudWatch Logs Insights is the appropriate feature for querying and analyzing application logs stored in CloudWatch Logs.

Question 176

A data engineer needs to join two datasets but wants all records from the first dataset, even when no matching record exists in the second dataset. Which SQL join should be used?

1. INNER JOIN
2. RIGHT JOIN only
3. LEFT JOIN
4. CROSS JOIN

Correct Answer: 3

Explanation:

A LEFT JOIN returns every row from the left table and matching rows from the right table when they exist. If a row in the left table has no matching record in the right table, the right-side columns are returned as NULL. This makes LEFT JOIN useful when the complete set of records from the first dataset must be preserved even when related data is missing. INNER JOIN would exclude unmatched records, while CROSS JOIN creates combinations of every row. Therefore, a LEFT JOIN is the correct SQL operation when all records from the first dataset must remain in the result.

Question 177

A company wants to ensure that data stored in S3 remains available even if an individual object is accidentally overwritten. Which S3 feature can help preserve previous versions?

1. S3 Versioning
2. S3 Transfer Acceleration
3. S3 Select
4. S3 Access Points

Correct Answer: 1

Explanation:

S3 Versioning preserves multiple versions of an object in the same bucket. When an object is overwritten or deleted, previous versions can remain available depending on the operation and configuration. This provides protection against accidental overwrites and deletions and can support recovery from unintended changes. Transfer Acceleration is designed to improve data transfer speeds, S3 Select allows applications to retrieve subsets of object data, and Access Points simplify controlled access to shared S3 data. Therefore, enabling S3 Versioning is the appropriate approach when a company wants to preserve previous versions of objects and support recovery from accidental modifications.

Question 178

A data engineer wants to use SQL to calculate the total sales amount for each customer. Which SQL clause is typically required to group records by customer?

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

Correct Answer: 2

Explanation:

The SQL GROUP BY clause groups rows that have the same values in one or more specified columns. When calculating total sales for each customer, the query can group records by customer_id and use an aggregate function such as SUM(sales_amount). This produces one aggregated result for each customer. ORDER BY sorts the final results, LIMIT restricts the number of rows returned, and DISTINCT removes duplicate combinations from the selected results. Therefore, GROUP BY is the appropriate SQL clause for grouping sales records by customer before calculating aggregate values such as total sales.

Question 179

A company wants to control who can access databases and tables in a governed AWS data lake. Which service provides centralized data lake permissions?

1. Amazon CloudFront
2. AWS Lake Formation
3. Amazon EBS
4. Amazon Route 53

Correct Answer: 2

Explanation:

AWS Lake Formation provides centralized governance and access control for data lakes. It allows administrators to manage permissions on data resources such as databases and tables and can provide fine-grained access controls for analytical workloads. Lake Formation integrates with services such as AWS Glue Data Catalog and Amazon Athena to help organizations govern access to shared datasets. CloudFront is used for content delivery, EBS provides block storage, and Route 53 provides DNS services. Therefore, AWS Lake Formation is the appropriate service when a company needs centralized permissions and governance for databases and tables in an AWS data lake.

Question 180

A data engineer needs to identify records that have NULL values in a specific SQL column. Which SQL condition should be used?

1. column = NULL
2. column == NULL
3. column IS NULL
4. column LIKE NULL

Correct Answer: 3

Explanation:

In SQL, NULL represents an unknown or missing value and cannot be compared using the standard equality operator. To identify rows where a column contains NULL, the correct condition is column IS NULL. Similarly, IS NOT NULL can be used to find rows where a value exists. Conditions such as column = NULL do not correctly identify NULL values because NULL comparisons evaluate using SQL’s three-valued logic. Therefore, IS NULL is the correct SQL condition for finding missing or undefined values in a column, making it especially useful during data quality checks and validation processes.