Question 1

A company's security team mandates that their Amazon RDS databases should only accept connections from specific, known IP addresses to ensure security. As a data engineer, you are tasked with implementing this requirement for an RDS instance that will be accessed by multiple clients located in different geographical locations, each with a fixed set of IP addresses.

Which of the following would be the most effective and secure way to comply with this security requirement?

Options :

A : Implement a network Access Control List (ACL) with rules to allow the known IP addresses and deny all others, applying these to the subnet associated with the RDS instance.

B : Configure AWS WAF with a set of rules to allowlist the specific IP addresses, and associate these rules with the RDS instance.

C : Utilize AWS Identity and Access Management (IAM) policies to restrict database access to the specific IP addresses.

D : Modify the inbound rules of the RDS instance-s security group to allow traffic from the known IP addresses and deny all other traffic.

Answer: D

Question 2

A medium-sized enterprise with fluctuating data analytics demands is exploring Amazon Redshift options. They are looking for a configuration that minimizes the need for active resource management, especially during unpredictable periods of high query volume. The ideal solution should adapt to changing demands while maintaining operational efficiency.

Which Redshift configuration should they consider to meet these requirements of adaptability and ease of management?

Options :

A : Choose Redshift Serverless, as it provides the flexibility to automatically adapt to changing query volumes without manual scaling.

B : Opt for Redshift with RA3 nodes, which offer scalable storage and compute capabilities, and configure auto-scaling policies to handle variable query loads.

C : Select Redshift with On-Demand pricing and set up scaling triggers based on performance metrics to manage varying loads efficiently.

D : Implement a traditional Redshift cluster with dense compute nodes, using dynamic resizing features for adapting to fluctuating workloads.

Answer: A

Question 3

A Data Engineering Consultant is reviewing the performance of an Amazon Redshift cluster used by a digital marketing agency. The cluster processes extensive user interaction and advertising campaign data. The consultant notes that, during specific aggregation queries involving a join between a user_activities table (distributed on user_id) and a campaigns table (distributed on campaign_id), certain nodes are running at high CPU utilization while others are barely used. These discrepancies in resource usage are leading to longer than expected query execution times.

What change can the consultant recommend to address this performance issue?

Options :

A : Convert the join operations in the aggregation queries to LEFT JOIN instead of INNER JOIN to ensure better CPU utilization.

B : Increase the Redshift cluster-s node count to provide additional resources and distribute the workload more evenly.

C : Switch the distribution style of the user_activities table to an even distribution to balance the load across all nodes.

D : Optimize the VACUUM operation to reorganize the data and improve query performance.

Answer: C

Question 4

A data engineering team is building a system that processes various types of events generated by different applications within their organization. The system needs to route these events to specific AWS services for processing and analysis based on the event type. The solution must be scalable and able to handle many events efficiently.

Which AWS service should the data engineering team use to route these events to the appropriate AWS services based on the type of event?

Options :

A : Use Amazon EventBridge to route events to target AWS services based on rules.

B : Use AWS Lambda to manually parse and dispatch events to other AWS services.

C : Use Amazon Kinesis Data Streams to filter and route the events to different AWS services.

D : Use AWS Step Functions to orchestrate the event routing process to various AWS services.

Answer: A

Question 5

A data engineer has a one-time task to read data from objects that are in Apache Parquet format in an Amazon S3 bucket. The data engineer needs to query only one column of the data. Which solution will meet these requirements with the LEAST operational overhead?

Options :

A :

Confiqure an AWS Lambda function to load data from the S3 bucket into a pandas dataframe- Write a SQL SELECT statement on the dataframe to query the required column.

B : Use S3 Select to write a SQL SELECT statement to retrieve the required column from the S3 objects.

C : Prepare an AWS Glue DataBrew project to consume the S3 objects and to query the required column.

D :

Run an AWS Glue crawler on the S3 objects. Use a SQL SELECT statement in Amazon Athena to query the required column.

Answer: B,D