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

 

Question 201

A data engineer needs to identify the highest sales amount in a dataset. Which SQL aggregate function should be used?

1. SUM()
2. COUNT()
3. MAX()
4. AVG()

Correct Answer: 3

Explanation:

The SQL MAX() aggregate function returns the highest value from a specified column. For example, SELECT MAX(sales_amount) FROM sales returns the largest sales amount in the dataset. SUM() calculates the total of numeric values, COUNT() counts rows or values, and AVG() calculates the average. Aggregate functions are commonly used during data analysis to summarize large datasets. Therefore, when the requirement is to identify the highest sales amount, MAX() is the correct function. The data engineer can also combine it with GROUP BY when the maximum value needs to be calculated separately for different categories or groups.

Question 202

A company wants to trigger an AWS Lambda function when a new object is uploaded to an Amazon S3 bucket. Which feature can be used?

1. S3 Event Notifications
2. S3 Glacier
3. S3 Object Lock
4. S3 Inventory

Correct Answer: 1

Explanation:

Amazon S3 Event Notifications can send notifications when specific events occur in a bucket, such as object creation. These events can be configured to invoke services such as AWS Lambda, send messages to Amazon SQS, or publish notifications through Amazon SNS. This enables event-driven processing where a new file can automatically trigger validation, transformation, or another workflow. S3 Glacier is a storage option, Object Lock protects objects from modification or deletion, and S3 Inventory provides reports about objects. Therefore, S3 Event Notifications are the appropriate feature for automatically triggering a Lambda function when a new object is uploaded.

Question 203

A data engineer wants to protect an S3 bucket from accidental public access. Which security control should be enabled?

1. S3 Transfer Acceleration
2. S3 Block Public Access
3. S3 Intelligent-Tiering
4. S3 Select

Correct Answer: 2

Explanation:

Amazon S3 Block Public Access provides controls designed to prevent buckets and objects from becoming publicly accessible through certain bucket or access point policies and ACL configurations. It is an important security control for data lakes and other S3 environments containing private or sensitive data. Enabling Block Public Access helps reduce the risk of accidental exposure caused by incorrect permissions. Transfer Acceleration improves transfer speeds, Intelligent-Tiering manages storage access tiers, and S3 Select allows retrieval of subsets of object data. Therefore, S3 Block Public Access is the appropriate security control when an organization wants to prevent accidental public exposure of S3 data.

Question 204

A data engineer needs to calculate the average transaction value for each customer. Which SQL combination should be used?

1. ORDER BY with LIMIT
2. DISTINCT with UNION
3. GROUP BY with AVG()
4. WHERE with JOIN only

Correct Answer: 3

Explanation:

To calculate an average transaction value for each customer, the query should group records by customer and apply the AVG() aggregate function. For example, SELECT customer_id, AVG(amount) FROM transactions GROUP BY customer_id calculates a separate average for each customer. GROUP BY creates the customer-level groups, while AVG() calculates the mean value within each group. ORDER BY and LIMIT are used for sorting and restricting results, DISTINCT removes duplicates, and UNION combines result sets. Therefore, using GROUP BY together with AVG() is the correct SQL approach for calculating average transaction values for individual customers.

Question 205

A company wants to continuously monitor a data processing application and collect logs and metrics for troubleshooting. Which AWS service should be used?

1. AWS KMS
2. Amazon CloudWatch
3. Amazon Macie
4. AWS Lake Formation

Correct Answer: 2

Explanation:

Amazon CloudWatch provides monitoring and observability capabilities for AWS resources and applications. It can collect and monitor metrics, logs, and events, allowing data engineers to identify errors, performance problems, and operational issues in data processing applications. CloudWatch Logs can store application logs, while metrics can be visualized through dashboards or monitored using alarms. AWS KMS manages encryption keys, Macie focuses on sensitive-data discovery, and Lake Formation provides data lake governance. Therefore, Amazon CloudWatch is the appropriate service for continuously monitoring an application and collecting logs and metrics needed for troubleshooting and operational visibility.

Question 206

A data engineer wants to make a large dataset available for analysis using SQL while keeping the original raw data unchanged. Which data lake design is most appropriate?

1. Replace the raw dataset with transformed data
2. Keep raw data in a raw zone and create transformed copies
3. Delete raw data after every transformation
4. Store only aggregated results

Correct Answer: 2

Explanation:

A well-designed data lake commonly preserves the original source data in a raw or landing zone while creating separate transformed and curated datasets for analytical use. Keeping the raw data unchanged provides an authoritative source that can be reprocessed if transformation logic changes or errors are discovered. It also supports auditing and traceability. Replacing raw data removes the ability to reproduce transformations, while deleting source data or keeping only aggregates can cause information loss. Therefore, maintaining raw data separately and creating transformed copies is the most appropriate architecture for preserving source information while making processed data available for SQL-based analysis.

Question 207

A data engineer needs to remove leading and trailing spaces from string values before loading them into a target table. Which SQL function can be used?

1. TRIM()
2. MAX()
3. COUNT()
4. SUM()

Correct Answer: 1

Explanation:

The SQL TRIM() function removes leading and trailing spaces from a string. This is useful during data cleaning when source systems contain inconsistent whitespace around values such as customer names, product codes, or addresses. For example, TRIM(customer_name) can normalize values before they are stored in a curated dataset. MAX() identifies the largest value, COUNT() counts records or values, and SUM() calculates totals. Therefore, TRIM() is the correct function for removing unnecessary spaces from string data. Data engineers commonly use it as part of transformation and validation processes to improve consistency and downstream data quality.

Question 208

A company wants to store large amounts of data in Amazon S3 and automatically reduce storage costs as objects become less frequently accessed. Which feature should be configured?

1. S3 Object Lock
2. S3 Intelligent-Tiering
3. S3 Versioning
4. S3 Access Points

Correct Answer: 2

Explanation:

S3 Intelligent-Tiering automatically moves objects between access tiers based on changing access patterns. This makes it useful when a company does not know exactly how frequently its data will be accessed over time. Frequently accessed objects can remain in an appropriate access tier, while objects that become less frequently accessed can move to lower-cost tiers. Object Lock protects objects from deletion or overwriting, Versioning preserves multiple versions, and Access Points provide dedicated access controls. Therefore, S3 Intelligent-Tiering is the best choice when the goal is to automatically optimize storage costs as object access patterns change.

Question 209

A data engineer wants to identify records that exist in one table but have no matching record in another table. Which SQL approach can be used?

1. LEFT JOIN with a NULL filter
2. CROSS JOIN
3. UNION without filtering
4. ORDER BY

Correct Answer: 1

Explanation:

A LEFT JOIN can be used to identify records that exist in the first table but have no corresponding record in the second table. After performing the LEFT JOIN, the query can filter for rows where a column from the right table is NULL. For example, WHERE right_table.id IS NULL identifies unmatched records from the left table. A CROSS JOIN produces combinations of all rows, UNION combines compatible result sets, and ORDER BY sorts results. Therefore, a LEFT JOIN combined with a NULL filter is an effective SQL technique for identifying records that are missing from a related table.

Question 210

A company needs to orchestrate several data processing steps where the output of one step determines whether the next step should run. Which AWS service is designed for this requirement?

1. Amazon S3
2. AWS Step Functions
3. Amazon Macie
4. AWS KMS

Correct Answer: 2

Explanation:

AWS Step Functions is a workflow orchestration service that allows data engineers to coordinate multiple processing steps. Workflows can contain sequential states, branching logic, retries, error handling, parallel execution, and other control mechanisms. For example, a workflow could run a Glue job, check its result, and then decide whether to start another job or move the data to a quarantine location. S3 provides object storage, Macie discovers sensitive data, and KMS manages encryption keys. Therefore, Step Functions is the appropriate service when multiple data processing tasks need to be coordinated based on the outcome of previous steps.

Question 211

A data engineer wants to reduce the cost of querying an S3 dataset with Amazon Athena. Which action directly reduces the amount of data scanned?

1. Add more IAM users
2. Use partitioning and compression
3. Increase the number of CloudWatch alarms
4. Disable columnar formats

Correct Answer: 2

Explanation:

Athena query costs are strongly influenced by the amount of data scanned. Partitioning allows Athena to skip data partitions that do not match query filters, while compression reduces the amount of data that needs to be read. Using columnar formats such as Parquet can further improve efficiency because Athena can read only the required columns. Adding IAM users or CloudWatch alarms does not reduce query scanning, and disabling columnar formats can increase the amount of data processed. Therefore, using appropriate partitioning and compression is an effective way to reduce the amount of data scanned and consequently reduce Athena query costs.

Question 212

A company wants to securely store encryption keys used to protect sensitive data in AWS services. Which AWS service should be used?

1. AWS Key Management Service (AWS KMS)
2. Amazon Athena
3. Amazon EventBridge
4. Amazon SQS

Correct Answer: 1

Explanation:

AWS Key Management Service (AWS KMS) is designed to create and manage cryptographic keys used by AWS services and applications. KMS integrates with services such as Amazon S3, Amazon Redshift, and Amazon EBS to provide encryption capabilities. It also supports access control through key policies and IAM permissions and provides auditing information through AWS CloudTrail. Athena is a query service, EventBridge provides event routing and scheduling, and SQS provides message queuing. Therefore, AWS KMS is the appropriate service for managing encryption keys used to protect sensitive information across AWS workloads.

Question 213

A data engineer needs to find all records where a customer email address is missing. Which SQL condition should be used?

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

Correct Answer: 2

Explanation:

SQL uses the IS NULL condition to identify fields that contain NULL values. NULL represents missing or unknown information and cannot be reliably compared using the equality operator. Therefore, a query such as SELECT * FROM customers WHERE email IS NULL correctly identifies customers whose email address is missing. Using email = NULL or email == NULL does not correctly test for NULL because SQL uses three-valued logic for NULL comparisons. LIKE NULL is also not an appropriate method. Therefore, IS NULL is the correct SQL condition for identifying records with missing email addresses.

Question 214

A company wants to discover sensitive information such as personally identifiable information in S3 objects. Which AWS service should be used?

1. Amazon Macie
2. Amazon CloudFront
3. Amazon SQS
4. Amazon Route 53

Correct Answer: 1

Explanation:

Amazon Macie is an AWS security service designed to discover and protect sensitive data stored in Amazon S3. It can identify potentially sensitive information such as personally identifiable information (PII) and provide visibility into where sensitive data exists. This can help organizations with privacy, security, governance, and compliance requirements. CloudFront is a content delivery service, SQS is a message queuing service, and Route 53 provides DNS services. Therefore, Amazon Macie is the appropriate choice when a company needs to discover sensitive information within S3 objects and gain better visibility into its sensitive-data exposure.

Question 215

A data engineer needs to combine two datasets while preserving every record from both datasets, including records that do not have matches. Which SQL join should be used?

1. INNER JOIN
2. LEFT JOIN
3. FULL OUTER JOIN
4. CROSS JOIN

Correct Answer: 3

Explanation:

A FULL OUTER JOIN returns all records from both tables. When matching records exist, their values are combined into the same result row. When a record exists in only one table, the columns from the other table contain NULL values. This makes FULL OUTER JOIN appropriate when the complete set of records from both datasets must be preserved, including unmatched records. INNER JOIN returns only matching records, while LEFT JOIN preserves all records from only the left table. CROSS JOIN creates combinations of every row. Therefore, FULL OUTER JOIN is the correct choice for preserving unmatched records from both datasets.

Question 216

A company wants to automatically start a daily ETL process at a specific time. Which service can provide the required schedule?

1. Amazon EventBridge Scheduler
2. Amazon Macie
3. AWS KMS
4. Amazon EBS

Correct Answer: 1

Explanation:

Amazon EventBridge scheduling capabilities can be used to run actions at specific times or recurring intervals. A data engineer can configure a daily schedule that invokes a supported target, such as a Lambda function, Step Functions workflow, or another AWS service involved in the ETL pipeline. This allows routine data processing to run automatically without manual intervention. Macie focuses on sensitive-data discovery, KMS manages encryption keys, and EBS provides block storage. Therefore, EventBridge Scheduler is an appropriate solution for initiating a daily ETL process at a specified time.

Question 217

A data engineer wants to ensure that an S3 object cannot be permanently deleted during a required compliance retention period. Which Object Lock mode provides stronger protection against deletion?

1. Governance mode
2. Compliance mode
3. Versioning mode
4. Lifecycle mode

Correct Answer: 2

Explanation:

Amazon S3 Object Lock Compliance mode provides strong protection for objects during a configured retention period. In Compliance mode, protected object versions cannot be overwritten or deleted by users, including users with special permissions, until the retention period expires. Governance mode also provides protection but allows authorized users with appropriate permissions to bypass or modify retention controls. Versioning and Lifecycle are separate S3 features and are not Object Lock modes. Therefore, Compliance mode is the appropriate choice when regulatory or compliance requirements require stronger immutability and prevent deletion during the specified retention period.

Question 218

A company wants to monitor AWS API activity and determine which IAM identity performed a particular action. Which CloudTrail information is most useful?

1. Event history
2. S3 Lifecycle configuration
3. Athena workgroup settings
4. Glue crawler schedule

Correct Answer: 1

Explanation:

AWS CloudTrail Event History provides a searchable record of recent management events and can show details about AWS API activity. These events can include information about the identity that performed an action, the API operation, the resource affected, and the time of the request. This information is useful when investigating security incidents, auditing user activity, or troubleshooting unexpected changes. S3 Lifecycle settings, Athena workgroups, and Glue crawler schedules do not provide the required audit trail for AWS API calls. Therefore, CloudTrail Event History is the appropriate source for determining which identity performed a particular AWS action.

Question 219

A data engineer wants to process only new records arriving in a database instead of repeatedly processing the entire table. Which approach is most appropriate?

1. Full load every time
2. Incremental processing using a change marker
3. Delete the source table
4. Disable database logging

Correct Answer: 2

Explanation:

Incremental processing allows a pipeline to process only records that have changed or arrived since the previous successful run. A data engineer can use a change marker such as a timestamp, sequence number, increasing ID, or CDC mechanism to identify new or modified records. This reduces processing time, compute requirements, and unnecessary data movement compared with repeatedly performing full loads. A full load processes the entire dataset each time, while deleting the source table or disabling logging does not provide a reliable incremental strategy. Therefore, incremental processing using an appropriate change marker is the recommended approach for efficiently handling newly arrived data.

Question 220

A company wants to ensure that a data pipeline can recover from temporary service failures without immediately failing the entire workflow. Which feature should be implemented?

1. Retry and error-handling logic
2. Disable all monitoring
3. Delete failed records
4. Remove all validation checks

Correct Answer: 1

Explanation:

Retry and error-handling logic improves the resilience of data pipelines by allowing temporary failures to be handled without immediately terminating the entire workflow. Transient issues such as throttling, temporary network problems, or short-lived service interruptions can often be resolved by retrying the operation with controlled delays and a maximum number of attempts. Workflow services such as Step Functions provide built-in retry and catch mechanisms that can be configured for individual states. Disabling monitoring or validation reduces reliability, while deleting failed records can cause data loss. Therefore, implementing retry and error-handling logic is the best approach for building a resilient pipeline.