Data-Engineer-Associate Exam Results

Concurrency scaling is a feature that allows you to support thousands of concurrent users and queries, with consistently fast query performance. When you turn on concurrency scaling, Amazon Redshift automatically adds query processing power in seconds to process queries without any delays. You can manage which queries are sent to the concurrency-scaling cluster by configuring WLM queues. To turn on concurrency scaling for a queue, set the Concurrency Scaling mode value to auto. The other optionsare either incorrect or irrelevant, as they do not enable concurrency scaling for the existing Redshift cluster on RA3 nodes. References:

Working with concurrency scaling - Amazon Redshift

Amazon Redshift Concurrency Scaling - Amazon Web Services

Configuring concurrency scaling queues - Amazon Redshift

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide (Chapter 6, page 163)

Problem Analysis:

Input Requirements: Gaming app generates approximately20 KB data records, which must be ingested and made available tothree internal consumerswithdedicated throughput.

Key Requirements:

High throughput for ingestion from each device.

Dedicated processing bandwidth for each consumer.

Key Considerations:

Amazon Kinesis Data Streamssupports high-throughput ingestion withPutRecords APIfor batch writes.

TheEnhanced Fan-Outfeature providesdedicated throughputto each consumer, avoiding bandwidth contention.

This solution avoids bottlenecks and ensures optimal throughput for the gaming application and consumers.

Solution Analysis:

Option A: Kinesis Data Streams + Enhanced Fan-Out

PutRecords API is designed for batch writes, improving ingestion performance.

Enhanced Fan-Out allows each consumer to process the stream independently with dedicated throughput.

Option B: Data Firehose + Dedicated Throughput Request

Firehose is not designed for real-time stream processing or fan-out. It delivers data to destinations like S3, Redshift, or OpenSearch, not multiple independent consumers.

Option C: Data Firehose + Enhanced Fan-Out

Firehose does not support enhanced fan-out. This option is invalid.

Option D: Kinesis Data Streams + EC2 Instances

Hosting stream-processing applications on EC2 increases operational overhead compared to native enhanced fan-out.

Final Recommendation:

UseKinesis Data Streams with Enhanced Fan-Outfor high-throughput ingestion and dedicated consumer bandwidth.

 AWS Glue is a fully managed serverless ETL service that can handle data deduplication with minimal operational overhead. AWS Glue provides a built-in ML transform called FindMatches, which can automatically identify and group similar records in a dataset. FindMatches can also generate a primary key for each group of records and remove duplicates. FindMatches does not require any coding or prior ML experience, as it can learn from a sample of labeled data provided by the user. FindMatches can also scale to handle large datasets and optimize the cost and performance of the ETL job. References:

AWS Glue

FindMatches ML Transform

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

To perform cross-Region snapshot copying of an encrypted Redshift cluster, AWS documentation and the exam study guide clearly outline two essential steps:

You must create a snapshot copy grant in thedestination Region.This allows Amazon Redshift to encrypt the snapshots using the specified AWS KMS key.

You must enable snapshot copying in thesource Regionand specify the name of the snapshot copy grant that was created in thedestination Region.

From the study guide:

“To enable cross-region copy of encrypted snapshots, you must create a snapshot copy grant in the destination Region and enable snapshot copying in the source Region by specifying the snapshot copy grant name.”

–Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf

OptionE(Multi-AZ deployment) is not applicable to Amazon Redshift, which does not support Multi-AZ configurations like Amazon RDS.