DEA-C01 Question 200
Select 3You are designing a data pipeline for a company that processes large volumes of clickstream data from its website. The data must be ingested in real-time, stored for long-term analysis, and queried using SQL-based tools. Which combination of AWS services should you use to meet these requirements?
- A
Amazon Kinesis Data Streams for ingestion and Amazon S3 for storage
- B
Amazon Redshift for ingestion and analysis
- C
Amazon Kinesis Data Firehose for ingestion and Amazon S3 for storage
- D
Amazon Athena for querying data stored in Amazon S3
- E
AWS Glue for real-time ingestion and Amazon DynamoDB for storage
Show answer and explanation
Correct answers: A, C, D
Explanation
For a real-time data pipeline, you need a service like Amazon Kinesis Data Streams or Kinesis Data Firehose to handle real-time ingestion. Amazon S3 is ideal for long-term storage due to its durability and scalability. Finally, Amazon Athena is the appropriate service for querying data stored in S3 using SQL-based tools. This combination provides an efficient and cost-effective architecture for processing, storing, and analyzing real-time clickstream data.
- A. Correct.
Amazon Kinesis Data Streams is a suitable service for real-time ingestion of streaming data, and Amazon S3 provides cost-effective, durable storage for large datasets.
- B. Incorrect.
While Amazon Redshift is excellent for analysis, it is not designed for real-time ingestion of streaming data.
- C. Correct.
Amazon Kinesis Data Firehose is a managed service for real-time data ingestion and can automatically deliver data to Amazon S3, which is ideal for long-term storage.
- D. Correct.
Amazon Athena allows you to run SQL-based queries directly on data stored in Amazon S3, making it a suitable choice for querying clickstream data.
- E. Incorrect.
AWS Glue is primarily used for ETL (Extract, Transform, Load) operations and does not support real-time ingestion. Similarly, Amazon DynamoDB is not optimized for large-scale analytical storage.