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Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions:

1. A company stores time-series data that is collected from streaming services in an Amazon S3 bucket. The company must ensure that only workloads that are deployed within the company ' s VPC can access the data.
Which solution will meet this requirement?

A) Use a network ACL on the VPC subnets to allow only specific resources to access the S3 bucket.
B) Create an S3 bucket policy that uses a condition to allow access only to traffic that originates from the company ' s VPC.
C) Apply a security group to the S3 bucket that allows connections only from the company ' s VPC CIDR block.
D) Define an IAM policy that denies access to all users unless the request originates from within the company ' s VPC.

2. A mobile gaming company wants to capture data from its gaming app. The company wants to make the data available to three internal consumers of the data. The data records are approximately 20 KB in size.
The company wants to achieve optimal throughput from each device that runs the gaming app. Additionally, the company wants to develop an application to process data streams. The stream-processing application must have dedicated throughput for each internal consumer.
Which solution will meet these requirements?

A) Configure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Host the stream-processing application for each internal consumer on Amazon EC2 instances.Configure auto scaling for the EC2 instances.
B) Configure the mobile app to call the PutRecordBatch API operation to send data to Amazon Data Firehose. Submit an AWS Support case to turn on dedicated throughput for the company ' s AWS account. Allow each internal consumer to access the stream.
C) Configure the mobile app to use the Amazon Kinesis Producer Library (KPL) to send data to Amazon Data Firehose. Use the enhanced fan-out feature with a stream for each internal consumer.
D) Configure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature with a stream for each internal consumer.

3. A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company ' s current level of performance.
Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A) Use Hadoop Distributed File System (HDFS) as a persistent data store.
B) Use Amazon S3 as a persistent data store.
C) Use x86-based instances for core nodes and task nodes.
D) Use Graviton instances for core nodes and task nodes.
E) Use Spot Instances for all primary nodes.

4. A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket.
The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility.
Which solution will meet these requirements with the LOWEST latency?

A) Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.
B) Configure the S3 bucket to send a notification to an AWS Lambda function when any new object is created. Use the Lambda function to publish the data to Amazon Aurora. Use Aurora as a source to create an Amazon QuickSight dashboard.
C) Use AWS Glue bookmarks to read sensor data from the S3 bucket in real time. Publish the data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.
D) Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Create a new Data Firehose delivery stream to publish data directly to an Amazon Timestream database. Use the Timestream database as a source to create an Amazon QuickSight dashboard.

5. A company uses an Amazon Redshift cluster as a data warehouse that is shared across two departments. To comply with a security policy, each department must have unique access permissions.
Department A must have access to tables and views for Department A. Department B must have access to tables and views for Department B.
The company often runs SQL queries that use objects from both departments in one query.
Which solution will meet these requirements with the LEAST operational overhead?

A) Group tables and views for each department into dedicated schemas. Manage permissions at the schema level.
B) Group tables and views for each department into dedicated databases. Manage permissions at the database level.
C) Update the names of the tables and views to follow a naming convention that contains the department names. Manage permissions based on the new naming convention.
D) Create an IAM user group for each department. Use identity-based IAM policies to grant table and view permissions based on the IAM user group.

Solutions: