A data engineering team manages a data lake on Amazon S3 using Apache Iceberg tables. They need to support concurrent writes from multiple Spark jobs in Amazon EMR and queries from Amazon Athena. The team is experiencing occasional write conflicts and wants to ensure data consistency without sacrificing query performance. Which Iceberg feature should the team enable?

Use a single writer process to avoid conflicts

Disable snapshot isolation to allow concurrent writes

Enable optimistic concurrency control with retries for conflicting writes

Use the Hive catalog instead of the Glue catalog for Iceberg tables

AWSCertified Data Engineer - Associate

Domain 2Objective 1

Task 2.1: Choose a Data Store DEA-C01 Practice Questions (Page 3)

Part of the Content Domain 2: Data Store Management domain, which accounts for 26% of the DEA-C01 exam. AWS does not publish an official question count, but from its 130-minute exam (~50–85 total, ~13–22 in this domain), expect 3–6 from this objective — we provide 23 practice questions to prepare you well beyond it. (estimate)

23questions here

5free pages

8concepts

26%of the exam

Questions 11–15

11foundation · easy
A data engineering team needs to store and query large volumes of structured data with complex SQL queries and high concurrency. Which AWS service is designed for this type of analytical workload?
Select an answer first
12foundation · easy
A data engineer needs to query data from an Amazon RDS for PostgreSQL database directly from an Amazon Redshift cluster without moving the data. Which Redshift feature supports this?
Select an answer first
13foundation · easy
A data engineer needs a fully managed, in-memory data store that provides microsecond read latency for a real-time application with key-value access patterns. Which AWS service is designed for this use case?
Select an answer first
14application · medium
A retail company has an Amazon Redshift data warehouse with sales data. The company also maintains a separate Amazon RDS for PostgreSQL database with customer profile data. The analytics team wants to run queries that join sales data in Redshift with customer data in RDS, without duplicating the customer data into Redshift. Which feature should the data engineer use?
Select an answer first
15expert · hard
A data engineering team manages a data lake on Amazon S3 using Apache Iceberg tables. They need to support concurrent writes from multiple Spark jobs in Amazon EMR and queries from Amazon Athena. The team is experiencing occasional write conflicts and wants to ensure data consistency without sacrificing query performance. Which Iceberg feature should the team enable?
Select an answer first

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Task 2.1: Choose a Data Store DEA-C01 Practice Questions (Page 3)

Questions 11–15

A data engineering team needs to store and query large volumes of structured data with complex SQL queries and high concurrency. Which AWS service is designed for this type of analytical workload?

A data engineer needs to query data from an Amazon RDS for PostgreSQL database directly from an Amazon Redshift cluster without moving the data. Which Redshift feature supports this?

A data engineer needs a fully managed, in-memory data store that provides microsecond read latency for a real-time application with key-value access patterns. Which AWS service is designed for this use case?

Keep studying — Content Domain 2: Data Store Management