AWS Certified Data Engineer Exam (DEA-C01) Practice Test 8

Free AWS Certified Data Engineer Associate Exam (DEA-C01) Practice Test 8 fits cloud operators who want to move from keeping accounts healthy to building data flows. AWS is the default cloud for a huge share of global companies, so admin experience already sits next to the tools data teams use. The DEA-C01 adds the data-engineering credential those teams ask about. Certification benefits include a role-change story, proof you can own data work, and better odds of AWS and data engineering job offers instead of another infrastructure ticket queue.

The pay step is often the point of the move. Junior data engineers may average about $72,000, with stronger offers near $105,000. Mid-level data engineers may earn $119,000 to $156,000. Senior data engineers may earn about $147,000 to $181,000 or more. Employers in this lane include Google, Microsoft, and Meta.

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Welcome to your AWS Data Engineer Associate – Test-08

Name

Phone

Q1. An IoT company is looking into data streaming services in AWS. They want to process data in near real-time, while also having the ability to replay data in the same order.

Which services would satisfy the company‘s requirements (SELECT TWO)?

Select 2 option(s):

Amazon Managed Streaming for Apache Kafka (MSK)

Kinesis Data Streams

SQS Queues

AWS Glue

SQS FIFO Queues

Q2. A tech firm is tasked with setting up a healthcare client‘s data lake. The repository has raw and refined zones, with a mandatory 2-year retention for raw data. The current solution processes data after it is saved to the raw zone. The raw data will not be used after it is initially processed.

Which option would you suggest for the MOST cost-effective solution for storing the raw data?

Select 1 option(s):

Set up the S3 bucket to use Intelligent-Tiering, with Deep Archive Access tier enabled for all uploaded objects.

Set up a lifecycle policy to transition the data to Glacier Deep Archive 1 day after object creation.

Upload all files to the bucket as Glacier Deep Archive storage class.

Use the S3 Standard storage class for all uploaded objects.

Q3. The company data analysts are routinely querying sales data using AWS Athena. Over time, the sales data has grown more complex. Further, as individual data analysts write their queries, variations in results due to programming errors have emerged. To simplify their queries, you are tasked with creating a view for the data analysts to simplify querying data.

Which of the following statements are true regarding views in this context (SELECT TWO)?

Select 2 option(s):

Views provide high potential for increased performance due to automatic query optimization and caching.

To replace an existing view, we must use DROP VIEW and then execute a CREATE VIEW statement.

The view is a logical table, so the query that defines a view runs each time the view is referenced in a query.

The view is a physical table, so its result is immediately available when the view is referenced in a query.

To replace an existing view, we can use the CREATE VIEW statement.

Q4. Which of the following statements is correct regarding Lake Formation tag-based access control (LF-TBAC) and LF-Tags?

Select 1 option(s):

A principal with multiple LF-Tags granted with a single grant can access resources as long as they have at least one of the LF-Tags.

LF-Tags can be assigned to resources when creating the resource.

LF-Tag creators must have IAM permissions to create and maintain LF-Tags.

LF-TBAC supports the use of wildcards with LF-Tags for assigning permissions.

Q5. A mobile gaming company wants to build a centralized streaming log ingestion solution. The solution must compress the log files and store them on Amazon S3. The number of users, and thus, the volume of log data varies throughout the day and is affected by various seasonal holidays. The solution must work in near real time.

Which solution will meet these requirements with the LEAST operational overhead?

Select 1 option(s):

Make the mobile apps send the log files to an input S3 bucket. Configure an S3 Event to notify a Lambda function on the arrival of the data. Implement the compression procedure on the Lambda function, and store the output on S3.

Make the mobile apps send the log files to Amazon Kinesis Data Firehose. Configure the Kinesis Data Firehose to invoke a Lambda function to compress the log files. Set the Kinesis Data Firehose to stream the compressed files to S3.

Make the mobile apps send the log files to an input S3 bucket. Create an AWS Glue ETL workflow triggered by an EventBridge event on data arriving to S3. Implement a job to compress the log files, and set the workflow to output them to S3.

Make the mobile apps send the log files to Amazon Kinesis Data Streams. Use Amazon EC2 instances with the Kinesis Client Library (KCL) installed to read the stream records. Implement the compression procedure on the EC2 instances, and store the output on S3.

Q6. An Internet-of-Things (IoT) solutions company needs to develop an application that would analyze real-time clickstream events from sensors. The company wants to use clickstream data to perform various tasks in separate applications. Each of these downstream applications would work independently and would need real-time access to the data.

Which of the following services would provide the best solution to capture the clickstream events from the source and also provide a feed of the data stream to the downstream applications?

Select 1 option(s):

Use Amazon Managed Service for Apache Flink (previously Kinesis Data Analytics) to facilitate multiple applications to consume the same streaming data concurrently

Use Kinesis Data Streams (KDS) to facilitate multiple applications to consume the same streaming data concurrently

Use Amazon SQS to facilitate multiple applications to consume the same streaming data concurrently

Use Amazon Kinesis Data Firehose to facilitate multiple applications to consume the same streaming data concurrently

Q7. A data engineer working for a financial services company has been tasked to integrate data quality checks into their ETL jobs without any additional custom code. The quality checks should include missing values, duplicates, and outliers.

Which AWS service supports creating checks on datasets?

Select 1 option(s):

Kinesis Data Firehose

AWS EMR

AWS SageMaker Data Wrangler

AWS Glue DataBrew

Q8. A data engineering team at a retail company manages a fleet of EC2 instances that make read-heavy database requests to a Multi-Availability Zone PostgreSQL DB cluster running on Amazon RDS. The team now wants to make the database cluster more resilient from a disaster recovery perspective.

As a Certified Data Engineer, what steps would you suggest to the engineering team (SELECT THREE)?

Select 3 option(s):

Connect the EC2 instances to the database cluster via an Amazon RDS proxy.

Reserve the Amazon RDS capacity in advance.

Use Amazon RDS cross-region read replicas.

Enable Amazon RDS Multi-Availability Zone backups.

Move the Amazon RDS cluster to run within a private VPC.

Q9. A company needs to update the security groups of their Amazon EC2 instances within a Virtual Private Cloud (VPC). Their goal is to allow traffic from a specific IP address range to access a specific port on the instances. Which option represents the correct approach for achieving this requirement?

Select 1 option(s):

Update the Network ACLs (NACLs) associated with the subnet to allow traffic from the specified IP address range on the required port.

Create a new security group with the desired inbound rule allowing traffic from the specified IP address range on the required port, and associate it with the EC2 instances.

Modify the outbound rules of the existing security group to allow traffic from the specified IP address range on the required port.

Use AWS Identity and Access Management (IAM) policies to grant the necessary permissions for the specified IP address range to access the EC2 instances.

Q10. A data analyst wants to explore data in the company data lake stored on Amazon S3. Given the scale of the data, they want to use not only Athena but Apache Spark for its distributed capabilities to speed-up the exploration.

Which Athena feature allows for the use of Apache Spark?

Select 1 option(s):

Athena parameterized queries

Athena query settings

Athena workgroups

Athena query editor

Q11. A company has a table in Amazon S3, which they would like to store in a more efficient format for querying using Athena. Currently, only a small subset of columns is usually queried from the table.

Which of the following statements would best satisfy the company‘s needs?

Select 1 option(s):

CREATE TABLE new_table WITH (
format = ‘AVRO‘,
write_compression = ‘GZIP‘
) AS SELECT * FROM old_table;

CREATE TABLE new_table WITH (
format = ‘TEXTFILE‘,
write_compression = ‘GZIP‘
) AS SELECT * FROM old_table;

CREATE TABLE new_table WITH (
format = ‘TEXTFILE‘
) AS SELECT * FROM old_table;

CREATE TABLE new_table WITH (
format = ‘Parquet‘,
write_compression = ‘SNAPPY‘
) AS SELECT * FROM old_table;

Q12. A company has a daily running ETL process, which processes transactions from a production database. The process is time-sensitive and must be completed within a specified time window. Currently, the company is in the process of migrating the ETL job to an AWS Glue Spark job.

As a Certified Data Engineer, what would be the most cost-efficient way to structure the Glue ETL job?

Select 1 option(s):

Set the execution class of the Glue job to STANDARD

Set the Glue job to use Spot instances

Set the Glue to version 2.0

Set the execution class of the Glue job to FLEX

Q13. A gaming company is developing a web-based game that streams updates, which are then transformed and published to a leaderboard. The solution should minimize overhead, be capable of handling traffic spikes, and store updates in a highly available database.

Which of the following solutions would best meet the requirements?

Select 1 option(s):

Stream updates to SQS with a fleet of EC2 instances, which transform the updates. Store processed updates in a DynamoDB table.

Stream updates to Kinesis Data Streams, with an intermediary Lambda function to transform the updates. Store processed updates in an RDS MySQL database.

Stream updates to SNS, with a Lambda function to consume and transform the updates. Store processed updates in an RDS MySQL database.

Stream updates to Kinesis Data Streams, with an intermediary Lambda function to transform the updates. Store processed updates in a DynamoDB table.

Q14. A financial company is experimenting with predicting the future price of oranges based on data they have on supply, demand, harvests, transportation costs and weather. The weather data, in particular, they have stored as a CSV file on Amazon S3 using the One-Zone Infrequent Access (IA) storage class. Among others, the CSV file contains temperature measurements from different areas, stored in columns like min and max (for minimum and maximum temperatures obtained, respectively). An analyst is querying the CSV file with S3 Select using the query SELECT s.area, s.min, s.max from S3Object s but the query is failing with a code 400 error. What is the most likely reason for the error?

Select 1 option(s):

The S3 Select does not support querying on CSV files.

The S3 One-Zone IA storage class does not support S3 Select.

The underlying service is unavailable.

An object column name is clashing with a reserved keyword.

Q15. A data engineer working for an analytics company is attempting to optimize their Athena queries, and has stumbled upon different file formats.

Which of the following statements is INCORRECT regarding file formats?

Select 1 option(s):

Apache Avro is columnar

Apache Parquet is columnar

Apache Parquet is splittable

Apache Avro is splittable

Q16. An organization is planning to migrate its Microsoft SQL Server 2017 database to Amazon Aurora. The data engineering team aims to assess the compatibility, automate schema conversion, and perform a homogeneous migration. Which combination of AWS services should be employed for this scenario?

Select 1 option(s):

AWS Snowball for data transfer and AWS Glue for schema conversion.

AWS DataSync for data transfer and AWS Schema Conversion Tool (SCT) for schema conversion.

Amazon FSx for Windows File Server for data transfer and AWS Database Migration Service (DMS) for schema conversion.

AWS Database Migration Service (DMS) for data migration and AWS Schema Conversion Tool (SCT) for schema conversion.

Q17. An online retailer has been contacted by multiple parties interested in their customer browsing behavior and purchase history. The online retailer is already storing such information on Amazon S3, and is interested in selling the data in an anonymized format to these parties.

Which AWS service will help the company monetize their data with the LEAST operational overhead?

Select 1 option(s):

AWS Batch

Amazon AppFlow

AWS Lake Formation

AWS Data Exchange

Q18. A healthcare provider manages vast amounts of patient data across multiple facilities and stores it in a centralized database. The medical research team requires a system that can stream data directly into the database while enabling SQL-based modifications for research purposes. Additionally, the system should support intricate data queries to expedite medical analyses. Moreover, the solution should include a business intelligence (BI) dashboard highlighting any irregular patient health patterns.

Which of the following solutions aligns best with the described requirements?

Select 1 option(s):

Use Amazon Kinesis Data Firehose to stream data to Amazon S3. Create a BI dashboard by using Amazon QuickSight that has Amazon Athena as a data source.

Use Amazon Kinesis Data Firehose to stream data to Amazon Redshift. Create a BI dashboard by using Amazon QuickSight that has Amazon Redshift as a data source.

Use Amazon Kinesis Data Streams to stream data to Amazon Redshift. Create a BI dashboard by using Amazon QuickSight that has Amazon Redshift as a data source.

Use Amazon Kinesis Data Streams to stream data to Amazon S3. Create a BI dashboard by using Amazon QuickSight that has Amazon Athena as a data source.

Q19. A healthcare company is attempting to build a secure data lake within AWS. They have read about AWS Lake Formation, which seems suitable for their needs.

As a Certified Data Engineer, can you instruct the company what feature AWS Lake Formation does NOT support?

Select 1 option(s):

Cross account access

Column- and row-level access control

Support for external sources

Support for logical expressions such as OR and Less than in Lake Formation Tags

Q20. An organization wants to use AWS CloudFormation to automate the provisioning of infrastructure containing EC2 instances, an RDS database and some S3 buckets. Which of the following statements is a best practice when working with AWS CloudFormation, ensuring consistent and efficient infrastructure management?

Select 1 option(s):

Avoid using parameters in CloudFormation templates to reduce complexity and ensure stability.

Use StackSets to deploy and update resources across multiple AWS accounts and regions.

Manually modify AWS resources created by CloudFormation outside of the CloudFormation stack for faster updates.

Define all resources in a single CloudFormation template to simplify management.

Q21. An insurance company stores terabytes of claim data on Amazon S3. Furthermore, the company data analysts are querying the data directly from S3 on a weekly basis using Amazon Redshift Spectrum. To design a cost optimization plan, a data engineer is tasked with first understanding how the data analysts are querying the data.

Which of the following monitoring view should the data engineer look into for solving the task?

Select 1 option(s):

SYS_EXTERNAL_QUERY_DETAIL

SYS_SERVERLESS_USAGE

SYS_LOAD_DETAIL

SYS_ANALYZE_HISTORY

Q22. A data engineer is designing the architecture of a Amazon Virtual Private Cloud (VPC) for data analytical workloads. They are worried about infrastructure security, and unsure about the main differences between security groups and network access control lists. Which of the following statements are true regarding security groups (SELECT TWO)?

Select 2 option(s):

Security groups are stateless: return traffic must be explicitly allowed by the rules

Security groups operate at the instance level

Security groups support both allow and deny rules

Security groups only support allow rules

Security groups operate at the subnet level

Q23. You are tasked with optimizing the storage format for a large-scale dataset in Amazon S3 for efficient query performance with Amazon Athena. The dataset primarily consists of several complex data types like structs, maps, and lists. Which of the following storage formats would be most appropriate to handle these complex data types efficiently while ensuring high query performance?

Select 1 option(s):

Apache Parquet

Avro

ORC (Optimized Row Columnar)

CSV

Q24. A serverless application requires AWS Lambda to store and access data persistently and across invocations. The data involves large binaries and needs to be shared across multiple Lambda functions quickly.

Given these requirements, which AWS Lambda data storage option is most suitable for this scenario?

Select 1 option(s):

Amazon S3

Ephemeral storage (i.e., /tmp)

Lambda layers

Amazon Elastic File System (EFS)

Q25. A video streaming company needs to deliver its video-on-demand content to millions of users. The videos are generally watched frequently soon after uploading, however, they will have vastly different access patterns, as time goes by. Old videos will not be accessed often, but they still need to be instantly accessed.

Which is the most cost-effective way of storing the videos for the given use case?

Select 1 option(s):

Use Amazon EFS to store the videos. Configure lifecycle-rules to move video files to EFS StandardInfrequent Access (Standard-IA) after 30 days.

Use Amazon S3 to store the videos. Configure Amazon S3 lifecycle-rules to transition objects from S3 Standard storage class to Standard-IA after 30 days.

Use Amazon EFS Intelligent-Tiering storage class to store the video files.

Use Amazon S3 Intelligent-Tiering storage class to store the videos.

Q26. A company is looking at establishing a Glue Data Catalog for their data sources. However, they do not know what types of crawlers Glue supports.

What type of crawler is NOT supported by AWS Glue?

Select 1 option(s):

Kinesis

MongoDB

JDBC

Q27. An investment firm receives financial statements to an Amazon S3 bucket. Once received, various calculations are performed using the data from the file, taking less than 5 seconds. Peak volume is encountered during earnings season, when around five thousand files can be uploaded during business hours.

Which of the following architectures should the investment firm adopt to ingest the data with the LEAST development time and cost?

Select 1 option(s):

Configure an object-created event notification for the S3 bucket to trigger an SNS topic. Using the fan-out pattern, push messages to SQS queues from each of which an EC2 instance receives the URI of the freshly arrived file to process it.

Configure an EventBridge rule to periodically trigger AWS Batch to process the received files

Configure an object-created event notification for the S3 bucket to activate Amazon Kinesis Data Streams for processing the received files

Configure an object-created event notification for the S3 bucket to invoke an AWS Lambda function to process the received files

Q28. A data analyst in charge of a Quicksight dashboard has recently moved to using queries based on Amazon Redshift materialized views provided by the data engineering team. The data analyst is confused because daily sales data should have been ingested, yet the sales data on the dashboard is still lagging.

Which steps should be taken to guarantee the dashboard data is always up-to-date while still maintaining low query times with the LEAST operational overhead?

Select 1 option(s):

Row-level security should be turned on.

The materialized view should be refreshed on demand, either manually or via the scheduler API.

The materialized view should be dropped and the data queried directly.

Autorefresh should be enabled for the materialized view.

Q29. The sales leadership at a retail company has tasked a data analyst with providing a consolidated view of the net sales from the company‘s suppliers. The sales data is only available as Excel .xls files. The files contain top-level information that needs to be discarded, and other transformations are needed as well. The solution is required to have the consolidated data available for consumption via an interactive dashboard.

How can the data analyst meet this requirement with the LEAST development time?

Select 1 option(s):

Upload the Excel files to S3. Use the data import feature to ingest the data from S3 to DynamoDB. Use the Amazon Athena DynamoDB connector to read from DynamoDB, performing any transformations in SQL in Athena. Visualize the data using Amazon Quicksight.

Upload the Excel files to S3. Create a DataBrew dataset pointing to the S3 data. Author the required transformations in DataBrew. Write the transformed data to S3. Visualize the transformed data using Amazon Quicksight.

Write a Lambda function in Python using the pandas library that reads an Excel file from S3, perform the required transformations, and write the output file as a Parquet file to S3. Create and S3 Event to trigger the Lambda function on file creation. Upload the Excel files to S3. Use Athena to read the output Parquet file. Visualize the data using Amazon Quicksight.

Q30. An internet service provider is conducting real-time log analysis using AWS Lambda to process data from a Kinesis Data Stream. The data team has observed that the Lambda function is struggling to keep pace with the incoming data from the Kinesis Data Stream.

Which of the following options will NOT help fix the issue (SELECT TWO)?

Select 2 option(s):

Increase the memory assigned to the Lambda function

Enable concurrent Lambda invocations by configuring parallelization factor

Increase the vCPU assigned to the Lambda function

Reducing the Lambda function‘s timeout duration

Assign reserved concurrency to a particular Lambda

Q31. A multinational company heavily relies on its AWS infrastructure, managing numerous resources across regions. The security team has concerns about the lack of visibility into resource configuration changes. They need an automated solution for tracking of these changes and also flagging non-compliant resources.

Which AWS service should the company consider for meeting these requirements?

Select 1 option(s):

AWS CloudWatch.

AWS EventBridge.

AWS CloudTrail.

AWS Config.

Q32. A sports betting company stores sensitive data on Amazon S3. As per the company policy, the data on S3 needs to be encrypted. Furthermore, the company needs to control who has access to which encryption keys.

Which of the following encryption mechanism is most suitable for these requirements, allowing the company to achieve their goal with the LEAST operational overhead?

Select 1 option(s):

Use server-side encryption with customer-provided keys (SSE-C)

Use CloudHSM

Use server-side encryption with AWS Key Management Service keys (SSE-KMS)

Use server-side encryption with Amazon S3 managed keys (SSE-S3)

Q33. A developer is maintaining multiple AWS Lambda functions implemented in Python. The developer has realized that most of the Lambda functions use similar functionality. Further, whenever they update this functionality, they are forced to update several Lambda functions.

How can the developer ease the maintenance of the Lambda functions following best practices with the LEAST operational overhead?

Select 1 option(s):

Set up a CI/CD pipeline to bundle dependencies to the Lambda functions as part of deployment

Use Lambda layers to promote code reuse across multiple functions

Use Amazon AppFlow to manage dependencies during Lambda function deployment

Use Amazon S3 for storing shared code and have the Lambda functions download them at runtime

Q34. A financial analyst is setting up Amazon Athena to generate tables for each report stored under the same prefix in Amazon S3. Having executed the CREATE TABLE statement in Athena with the specified columns and their respective data types, the analyst has executed a SELECT query. To their surprise, the query yields zero records.

What is the correct approach for configuring the Amazon S3 location path?

Select 1 option(s):

S3 table location should be similar to s3://doc-example-bucket/table1.csv and s3://doc-example-bucket/table2.csv

S3 table location path should be similar to s3://doc-example-bucket/myprefix//input//

S3 file names should be similar to s3://doc-example-bucket/athena/inputdata/_file1

Add individual S3 prefixes for each table similar to s3://doc-example-bucket/table1/table1.csv and s3://doc-example-bucket/table2/table2.csv

Q35. A financial services company uses Amazon S3 as the data lake to store the input data that is ingested from a mobile application on a daily basis. The ingested data has attributes such as the client ID, the timestamp of the event, the source IP address, etc. The company processes millions of records daily and aims to run complex analytical queries on this data every day to enhance applications.

What is the most efficient method for storing this data on S3 to achieve optimal performance when processing millions of data points on a daily basis?

Select 1 option(s):

Partition the data by date, store the data in .csv format.

Partition the data by client ID, store the data in .csv format.

Partition the data by client ID, store the data in Apache Parquet format.

Partition the data by date, store the data in Apache ORC format.

Q36. An analytics company maintains an ETL application, which processes data from an on-premises NAS after it is uploaded. The application has been written in Apache Spark and results are written back to the same NAS. The data does not get often accessed, after being processed. A data engineer working for an analytics company has been tasked to migrate the application to the cloud using AWS. The solution should be serverless.

Which services should the engineer use for storage and processing for the LEAST costs and operational overhead (SELECT TWO)?

Select 2 option(s):

Amazon S3

Amazon EMR

Amazon EFS

AWS Glue

Amazon EBS

Q37. A financial company is running a large data lake that is constantly updated with new data. For upcoming regulatory requirements, the company wants to gain comprehensive and organization-wide visibility into the sensitivity of their data using Amazon Macie.

Which of the following statements regarding Amazon Macie are true (SELECT THREE)?

Select 3 option(s):

Macie can analyze S3 objects in any S3 storage class

Macie only supports various plain text formats like CSV, but no binary formats such as Apache Parquet

Automated discovery settings only apply to the current AWS Region. For additional regions, automated discovery mus tbe enabled and configured separately

If an S3 object is encrypted, Macie can analyze it only if it‘s encrypted with a key that Macie can access and is allowed to use

To be eligible for selection and analysis, an S3 object must be classifiable meaning it uses a supported storage class and its file name extension is supported

Q38. A data engineer is building an AWS Glue DataBrew recipe step for transforming .csv data stored on an Amazon S3 bucket. Specifically, the .csv file holds entries of movies with columns movie_id, title, director, and genre. The recipe should convert the rows to a single column with values like:

{
“movie_id“: 147,
“title“: “Forrest Gump“,
“directory“: “Robert Zemeckis“,
“genre“: “Drama“
}
Which of the following AWS Glue DataBrew recipes is the most suitable for the described conversion?

Select 1 option(s):

PIVOT

NEST_TO_ARRAY

NEST_TO_MAP

COALESCE

Q39. A data engineer working for a technology company has been tasked to create an application, which can consume streaming data, transform the streaming data, and save it into Amazon S3. The solution should automatically scale to different flow rates of data.

Which combination of steps should the engineer take to achieve their goal with the LEAST costs?

Select 1 option(s):

Consume data using on-demand Kinesis Data Streams with destination set to Amazon S3. Use S3 Events to trigger a Lambda function, which processes the delivered objects and saves them back to the S3 bucket.

Consume data using Kinesis Data Firehose, with an intermediary AWS Lambda function to transform the streaming data before saving it to Amazon S3.

Consume data using on-demand Kinesis Data Streams, with an intermediary AWS Lambda function to transform the streaming data before saving it to Amazon S3.

Consume data using Kinesis Data Firehose with destination set to Amazon S3. Use S3 Events to trigger a Lambda function, which processes the delivered objects and saves them back to the S3 bucket.

Q40. A retail company has been exploring AWS as a solution for their ETL pipelines, as currently they have to maintain multiple on-premises environments for their various ETL jobs. They have been looking at AWS Glue, as a solution for their hard-to-maintain environments.

As a Certified Data Engineer, which of the following are antipatterns for AWS Glue (SELECT TWO)?

Select 2 option(s):

Serverless processing.

Processing small datasets.

Multiple ETL engines.

Long-running jobs.

Configurable Spark environment.

Q41. An analytics company has an ETL workflow, which they would like to orchestrate daily. The ETL workflow consists of Glue and EMR jobs.

Which of the following services would allow orchestrating the ETL workflow with the LEAST operational overhead and costs?

Select 1 option(s):

Step Functions

Managed Workflows for Apache Airflow (MWAA)

Glue Workflows

Lambda

Q42. A news website is considering modernizing its content management system which currently relies heavily on relational databases. As they require schema flexibility, scalability and the ability to handle user-generated content, they are looking into AWS DynamoDB.

Which of the following statements are considered best practice when working with DynamoDB?

Select 2 option(s):

Use high-cardinality attributes, like employee_no, customer_id, or order_id for partition keys

Cache popular items for high read traffic using DynamoDB Accelerator (DAX)

Use low-cardinality attributes like Product_SKU as the partition key and Order_Date as the sort key

Always prefer parallel scans to sequential scans

When migrating from relation databases, use sequences or unique IDs generated by the DB engine as the partition key

Q43. After a data leak incident, it was discovered that sometimes for ad-hoc queries company employees had uploaded Excel files containing personally identifiable information (PII) on their customers to Amazon S3. While against company policies, this resulted in negative press for the company which now wants to detect and clean ungoverned PII from S3.

As an AWS Certified Data Engineer, which of the following solutions do you recommend to achieve this task with the LEAST operational overhead?

Select 1 option(s):

Use AWS Glue DataBrew to detect PII in the Excel files.

Write and run a Lambda function to convert the Excel files to CSV files. Use Amazon Macie to detect PII in the CSV files.

Write and run a Lambda function to convert the Excel files to CSV files. Use CloudTrail to detect PII in the CSV files.

Use Amazon Macie to detect PII in the Excel files stored on S3.

Q44. A data engineer working for a retail company has created an ETL script using AWS Glue, which saves the processed results to a DynamoDB table. The resulting schema can change over time, and the engineer has been instructed to also store the table within AWS Glue Data Catalog.

How should the engineer update the schema of the Data Catalog table with the LEAST operational overhead?

Select 1 option(s):

Schedule a Glue Crawler to run on a daily schedule.

Run the command MSCK REPAIR TABLE after the data is processed within the ETL script.

Manually update the table using AWS Glue console.

Create a Glue Workflow with a crawler step after the ETL job.

Q45. The data engineering team has set up the following IAM policy. What does the policy do?

{
“Version“: “2012-10-17“,
“Statement“: [
{
“Sid“:“Sid0“,
“Action“: [
“redshift:*“
],
“Effect“: “Allow“,
“Resource“: “arn:aws:redshift:us-west-2:*“
},
{
“Sid“:“Sid1“,
“Action“: [
“redshift:Delete*“
],
“Effect“: “Deny“,
“Resource“: “arn:aws:redshift:us-west-2:*“
}
]
}

Select 1 option(s):

The policy allows access to delete all Redshift resources in us-west-2, but denies all other Redshift actions within us-west-2.

Applying to all Redshift resources in us-west-2, the policy allows access to all Redshift actions except the action names starting with Delete which are denied.

Applying to all Redshift resources in us-west-2, the policy allows access to all Redshift actions on the 17th of October, 2012.

Applying to all Redshift resources in us-west-2, the policy allows access to all Redshift actions.

Q46. A data engineer at a company is considering the construction of an AWS Step Functions workflow to apply the same task to each dataset item.

Which state should they use for such a step in the workflow graph?

Select 1 option(s):

Parallel

Map

Wait

Choice

Q47. A data engineer at an analytics company has been tasked to provision the correct amount of read capacity units (RCU) for a DynamoDB table. A process will read from the DynamoDB table at a rate of 6 times per second, and the items will be 5 KB in size. Eventually consistent reads will be enough for the process.

How many RCU should the engineer provision for the table?

Select 1 option(s):

Q48. A company is looking at expanding their suite of used no-code tooling for their analysts. Currently, they are exploring the possibility of using AWS Glue DataBrew to create ETL jobs, with low barrier to entry.

As a Certified Data Engineer, which of the following statements are INCORRECT regarding DataBrew (SELECT TWO)?

Select 2 option(s):

DataBrew jobs must be scheduled using EventBridge rules.

DataBrew can be used to encrypt or mask PII data.

A DataBrew recipe can include up to 100 data transformations.

DataBrew jobs can be monitored using CloudWatch.

DataBrew does NOT offer data quality validation.

Q49. A data engineer at a company has been tasked to track external IP addresses when a third party uploads files to an Amazon S3 bucket managed and owned by the company.

Which of the following settings is a requirement to implement the requested tracking?

Select 1 option(s):

Enable VPC Flow Logs.

Enable S3 Event Notifications.

IP addresses of requests are tracked by default, so no setting needs to be enabled.

Enable Amazon S3 server access logging.

Q50. A company is looking to tighten its security measures on AWS, by moving some of its applications to a private VPC. However, some of their applications use other AWS services.

As a Certified Data Engineer, can you instruct the company on what AWS service does NOT have a VPC Interface Endpoint available?

Select 1 option(s):

Lambda

Kinesis

SQS

DynamoDB

Q51. A growing e-commerce company is considering the use of Amazon Redshift to support their increasing business intelligence, reporting and analytics needs. Which statements regarding Amazon Redshift are true (SELECT THREE)?

Select 3 option(s):

The Amazon Redshift query optimizer uses primary key and foreign key constraints between tables to generate more efficient query plans.

Amazon Redshift does not enforce unique, primary-key, and foreign-key constraints.

Redshift is a petabyte scale data warehouse, so it‘s better to use say CHAR(64) than CHAR(2) for storing a two-letter symbol.

Primary keys and foreign keys should be declared only if an ETL process or some other process enforces their integrity.

Amazon Redshift enforces unique, primary-key, and foreign-key constraints.

You need to choose a suitable sort key for your table, even if using automatic table optimization.

Q52. A data engineer has used Athena to create a table for a set of data stored in Apache Hive format in Amazon S3. The data in S3 is currently partitioned by date as follows:

s3://my-bucket/dt=2009-04-12/
The engineer queries the newly created table with the following query:
SELECT dt,impressionid FROM impressions WHERE dt > ‘2009-04-12‘
However, the query does not seem to be returning the correct results.
What should the engineer do to resolve their issue?

Select 1 option(s):

Run MSCK REPAIR TABLE impressions.

Run ALTER TABLE impressions ADD PARTITION (dt=‘2009-04-12‘) location ‘s3://my-bucket/dt=2009-04-12/‘ for all the existing partitions.

Query the data as follows:
SELECT dt,impressionid
FROM impressions
WHERE PARTITION(dt) > ‘2009-04-12‘.

Query the data as follows:
SELECT dt,impressionid
FROM impressions.
And manually filter the data from the result.

Q53. An analytics company has set up their data lake in Amazon S3, which acts as a base for their analytics applications. A data engineer has been tasked to create a table from an existing, which only includes a specific subset of columns. The created table will be used in analytics tasks, which usually require a subset of dates from the table. The solutions should optimize the performance of their application.

Which of the following queries should the engineer run using Athena to achieve their requirements?

Select 1 option(s):

CREATE TABLE new_table
WITH (
format = ‘AVRO‘,
location = ‘s3://bucket/new_location/‘,
partitioning = dt,
) AS SELECT key1, col1, col2, date FROM old_table;

CREATE TABLE new_table
WITH (
format = ‘PARQUET‘,
location = ‘s3://bucket/new_location/‘,
partitioning = ARRAY[‘dt‘],
) AS SELECT key1, col1, col2, date FROM old_table;

CREATE TABLE new_table
WITH (
format = ‘AVRO‘,
location = ‘s3://bucket/new_location/‘,
partitioning = ARRAY[‘dt‘],
) AS SELECT key1, col1, col2, date FROM old_table;

CREATE TABLE new_table
WITH (
format = ‘PARQUET‘,
location = ‘s3://bucket/new_location/‘,
partitioning = dt,
) AS SELECT key1, col1, col2, date FROM old_table;

Q54. An analytics company is looking at multiple options for their data warehousing. They are currently investigating Amazon Redshift as an option for their new data warehouse.

Which of the following options are NOT ideally suited for Redshift (SELECT THREE)?

Select 3 option(s):

Partitioned data

Online analytical processing (OLAP)

Online transactional processing (OLTP)

Unstructured data

BLOB data

Q55. An application developed by the software engineering team requires access to an Amazon Redshift database maintained and controlled by the data engineering team. They are considering allowing the application to access the database via the Redshift Data API. Which of the following are valid authentication methods for the Redshift Data API (SELECT TWO)?

Select 2 option(s):

Use temporary credentials obtained via the IAM identity

Use temporary credentials obtained via multi-factor authentication (MFA)

Use a username and password stored as SecureString in AWS Systems Manager Parameter Store

Use a username and password stored in AWS Secrets Manager

Use a username and password stored as String in AWS Systems Manager Parameter Store

Q56. A company is looking into backup options on AWS. They are currently investigating the use of AWS Backup.

As a Certified Data Engineer, which of the following services is NOT supported by AWS Backup?

Select 1 option(s):

Amazon Keyspaces

Amazon DocumentDB

Amazon Neptune

Amazon Aurora

Q57. A large retail company is looking for a service to manage its orchestration of data workflows in AWS. The company needs to be able to define complex workflows and use multiple computation platforms for its ETL jobs. They also want to be able to define its orchestration workflows in Python.

As a Certified Data Engineer, what service would you recommend to the company?

Select 1 option(s):

AWS EMR

Amazon Managed Workflows for Apache Airflow (MWAA)

AWS Step Functions

AWS Glue

Q58. A data engineer working for a retail company is working on a Kinesis Data Streams application. The application has multiple consumers, and they notice that their consumer record processing is falling behind.

Which of the following options should first be attempted to resolve their issue?

Select 1 option(s):

Rewrite the application with SNS instead of Kinesis Data Streams.

Increase the amount of shards in Kinesis Data Streams.

Use Kinesis Enhanced Fan-Out with the Kinesis Client Library to consume the records.

Increase WCU in DynamoDB checkpointing table.

Q59. An analytics company is planning on a large scale cloud transition to AWS. They are currently in the process of exploring, what resources and services they will need to transition to the cloud.

Which of the following services can best help the company achieve their requirements?

Select 1 option(s):

AWS Database Migration Service

AWS DataSync

AWS Transfer Family

AWS Application Discovery Service

Q60. In the context of Amazon Athena, which of the following query optimization techniques are according to best practices (SELECT TWO)?

Select 2 option(s):