DEA-C01 Data Ingestion and Transformation Practice Question
A financial services company ingests real-time stock trade data from multiple exchanges into Amazon Kinesis Data Streams. Each trade record is a JSON object with fields: trade_id, symbol, price, quantity, timestamp. The stream has 5 shards. The data is consumed by an AWS Lambda function that aggregates trades per symbol every minute and writes the results to an Amazon DynamoDB table for a real-time dashboard. Recently, the dashboard has been showing outdated data, and the Lambda function is experiencing high error rates. The CloudWatch logs show 'ProvisionedThroughputExceededException' errors from DynamoDB. The DynamoDB table has 10 read capacity units (RCU) and 10 write capacity units (WCU). The average trade volume is 5,000 trades per second across all symbols, and there are 100 symbols. The Lambda function is configured with a batch size of 100 and a 1-minute window. The data volume is expected to double in the next month. As a data engineer, what is the most appropriate course of action?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the DynamoDB write capacity units to 100 and enable auto scaling
The DynamoDB table is throttling due to insufficient write capacity. With 5,000 trades/s and updating per symbol per minute, the write rate is about 100 writes per minute (one per symbol), but the aggregation may cause bursts. However, the 'ProvisionedThroughputExceededException' indicates WCU is too low. Increasing WCU to 100 resolves the immediate issue; auto scaling handles future growth. Option A (switch to S3 and Athena) changes the architecture and loses real-time capabilities. Option B (increase shards) addresses Lambda concurrency but not DynamoDB throttling. Option D (use Firehose and QuickSight) is for delivery to S3, not real-time dashboard.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch the storage from DynamoDB to Amazon S3 and use Amazon Athena for the dashboard
Why it's wrong here
This changes the architecture from real-time DynamoDB updates to batch S3 storage, losing the real-time dashboard capability and introducing latency.
- ✗
Increase the number of Kinesis shards to 10 to increase Lambda concurrency
Why it's wrong here
Increasing Kinesis shards increases Lambda concurrency but does not address DynamoDB write capacity throttling, so the error persists.
- ✓
Increase the DynamoDB write capacity units to 100 and enable auto scaling
Why this is correct
Correct. The DynamoDB table is throttling writes; increasing WCU to 100 and enabling auto scaling resolves the current issue and accommodates future growth.
- ✗
Use Amazon Kinesis Data Firehose to deliver data to S3 and use Amazon QuickSight for the dashboard
Why it's wrong here
Using Kinesis Firehose to deliver to S3 is for near-real-time data lakes, not for a real-time dashboard that requires low-latency writes to DynamoDB.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.