Question 1

A company plans to move 10 TB of multimedia content from their local servers to AWS, with a portion of the data being updated weekly. These updates must be reflected in the Amazon S3 bucket where the data will be stored. The multimedia content consists of large image and video files.

To automate and schedule these data transfers effectively, which AWS service should the company employ?

Options :

A : Use AWS Transfer for SFTP to secure and automate data transfer to S3.

B : Use AWS DataSync to automate and schedule the ongoing transfer of files to Amazon S3.

C : Set up an AWS Snowball job for periodic data transfer to Amazon S3.

D : Deploy an AWS Storage Gateway to synchronize and manage data transfers to S3.

Answer: B

Question 2

A high-traffic news website is experiencing performance issues due to frequent, read-heavy queries to their main database, which stores frequently accessed user session data and website preferences. To enhance the website's responsiveness and reduce database load, they require a caching solution that provides high throughput and low latency for data retrieval.

Which AWS service should the website implement to efficiently cache frequently accessed data and improve application performance?

Options :

A : Configure Amazon S3 with Amazon CloudFront for caching static user session data and website preferences.

B : Implement Amazon ElastiCache to cache frequent read-query results and reduce direct database queries.

C : Deploy Amazon Relational Database Service (RDS) with read replicas to distribute the load of read queries.

D : Deploy Amazon DynamoDB with DAX (DynamoDB Accelerator) for caching read-heavy query results.

Answer: B

Question 3

A company is using Amazon Redshift for their business analytics and reporting purposes. They frequently need to run analytical queries on their historical data stored in a PostgreSQL database hosted on Amazon RDS. The company wants to analyze this historical data in conjunction with their current data warehouse data without moving or duplicating the data.

Which Redshift feature should the company use to meet this requirement?

Options :

A : Use Amazon Redshift federated queries to query the historical data in the PostgreSQL database in real-time alongside the warehouse data.

B : Configure AWS Database Migration Service (DMS) to replicate data continuously from the PostgreSQL database to the Amazon Redshift cluster.

C : Set up Amazon Redshift Spectrum to query the historical data directly from the PostgreSQL database on Amazon RDS.

D : Implement Amazon Redshift materialized views to periodically sync and store the historical data from the PostgreSQL database.

Answer: A

Question 4

A retail company receives a daily .xls file with customer data, which is uploaded to Amazon S3. The file size is about 2 GB. A data engineer is tasked with combining the customer first name and last name fields and then identifying the total number of unique customer entries in the file.

Which AWS service or feature should the data engineer use to determine the count of distinct customers with minimal operational effort?

Options :

A : Employ Amazon S3 Select to perform the concatenation and distinct count directly on the S3 file.

B : Utilize AWS Lambda with Amazon S3 trigger to process the file and calculate the number of distinct customer names.

C : Use Amazon Athena to run a SQL query that concatenates the names and counts distinct entries after converting the file to CSV format.

D : Set up an AWS Glue DataBrew job to concatenate the fields and use the COUNT_DISTINCT function to find the number of unique customers.

Answer: D

Question 5

A company wants to migrate an application and an on-premises Apache Kafka server to AWS. The

application processes incremental updates that an on-premises Oracle database sends to the Kafka server. The

company wants to use the replatform migration strategy instead of the refactor strategy.

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

Options :

A : Amazon Kinesis Data Streams

B : Amazon Managed Streaming for Apache Kafka (Amazon MSK) provisioned cluster

C : Amazon Data Firehose

D : Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless

Answer: D