Question 1

An enterprise is using Amazon Redshift for its data warehousing needs. Recently, they have observed intermittent query performance issues. The Data Engineering Team needs to regularly monitor and analyze query performance to identify potential bottlenecks.

Which combination of actions and AWS services should the data engineering team use to effectively monitor and optimize query performance?

Options :

A : Implement AWS CloudWatch to monitor the performance metrics of Amazon Redshift and use AWS Trusted Advisor for query optimization suggestions.

B : Set up Amazon Redshift Spectrum for extended query analysis and leverage AWS X-Ray for monitoring performance issues and bottlenecks.

C : Use Amazon Redshift Query Performance Insights to monitor query performance and Amazon Redshift Advisor for recommendations on performance optimization.

D : Utilize Amazon QuickSight for visualizing Redshift performance metrics and apply Amazon Redshift Query Editor for performance tuning.

Answer: C

Question 2

A data engineer is using Amazon Athena for querying customer engagement data stored in Amazon S3. The analyst needs to extract information about customer interactions for the year 2023 from a table called interaction_data. The initial query designed to fetch the total interactions per customer for 2023 is not yielding results for some customers known to have interactions in that year. The query needs adjustment to correctly reflect the entire dataset.

The original query is:

SELECT customer_id, sum(interactions)

FROM interaction_data

WHERE year = 2023

GROUP BY customer_id

How should the data engineer modify the Athena query to ensure it includes all relevant customer data for 2023?

Options :

A : Replace WHERE year = 2023 with a more inclusive condition, such as WHERE year >= 2023, to capture late-recorded data.

B : Introduce a CASE statement within the SUM function to handle any null values in the interactions column.

C : Include a subquery to first select distinct customer IDs from the interaction data, then sum interactions for those customers.

D : Add a LEFT JOIN with another table that lists all customers, ensuring inclusion of customers with zero interactions.

Answer: D

Question 3

A Data Engineering Team needs to help the security team to deliver logs from various AWS services in their production AWS account to a centralized logging AWS account for security analysis. They plan to use Amazon Kinesis Data Streams for real-time log processing and delivery.

To ensure secure and efficient log delivery between accounts, where should the Kinesis Data Stream be deployed and what security considerations should be taken into account?

Options :

A : Set up the Kinesis Data Stream in the production account and configure it to push logs directly to the centralized logging account.

B : Implement the Kinesis Data Stream in the production account and use AWS Lambda for cross-account delivery of logs to the centralized logging account.

C : Deploy the Kinesis Data Stream in the centralized logging account and establish cross-account access for the production account to write logs to the stream.

D : Deploy Kinesis Data Streams in both accounts, using one for collecting logs and the other for receiving and processing these logs.

Answer: C

Question 4

A company stores sensitive documents in an Amazon S3 bucket. They need to ensure that these documents can only be accessed by requests originating from a specific range of IP addresses within their corporate network. The company wants to enforce this policy at the bucket level.

Which approach should the company use to restrict access to the S3 bucket based on the originating IP address?

Options :

A : Apply an S3 bucket policy that includes a condition to allow access only from the specified IP address range.

B : Implement IAM user policies to restrict access to the S3 bucket based on the IP address.

C : Set up a Security Group attached to the S3 bucket to allow traffic only from the specified IP range.

D : Use a Network Access Control List (NACL) to restrict access to the S3 bucket for the specific IP range.

Answer: A

Question 5

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