DEA-C01 Matching — 10 Questions

Question 1

Match each AWS security service to its purpose in data protection.

Accepted Answer

AWS KMS: Manage encryption keys for data at rest and in transit. The correct matches are: AWS KMS for encryption key management, AWS IAM for access control, and AWS CloudTrail for API auditing. Common confusions include swapping these services' purposes.

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AWS KMS: Control access to AWS resources through users, groups, and roles

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AWS IAM: Manage encryption keys for data at rest and in transit

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AWS CloudTrail: Manage encryption keys for data at rest and in transit

Question 2

Match each AWS database service to its primary use case.

Accepted Answer

Amazon RDS: Relational database for online transaction processing (OLTP) workloads.. Correct matches: RDS -> OLTP relational, DynamoDB -> NoSQL low-latency, Redshift -> data warehousing, ElastiCache -> in-memory caching. Common confusions include swapping RDS and DynamoDB use cases.

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Amazon RDS: NoSQL key-value database for low-latency applications.

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Amazon DynamoDB: Relational database for OLTP workloads.

Question 3

Match each AWS storage class to its description.

Accepted Answer

S3 Standard: Designed for frequently accessed data with low latency and high throughput.. Correct matches: S3 Standard for frequently accessed data, S3 Intelligent-Tiering for automatic cost optimization, and S3 Glacier for archival. Common confusions involve mixing up Standard-IA and Glacier Deep Archive definitions.

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S3 Standard-IA: Lowest-cost storage class for long-term retention with retrieval times of 12 hours.

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S3 Glacier Deep Archive: For data accessed less frequently but requires rapid access when needed.

Question 4

Match each AWS service to its primary purpose in data engineering.

Accepted Answer

Amazon S3: Object storage for data lakes. The correct matches are: Amazon S3 → object storage for data lakes (A), AWS Glue → serverless ETL (B), Amazon Athena → interactive SQL queries on S3 (C), and Amazon Redshift → data warehousing (D). Common confusions involve mixing up services like Kinesis (streaming) with Glue (ETL) or Data Pipeline (orchestration) with Kinesis (ingestion).

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AWS Kinesis: Serverless ETL service

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AWS Data Pipeline: Real-time data ingestion

Question 5

Match each AWS networking concept to its definition.

Accepted Answer

VPC: A virtual network dedicated to your AWS account.. Networking fundamentals for AWS: VPC is a virtual network, subnets are subdivisions, security groups are instance-level firewalls, and NACLs are subnet-level stateless firewalls.

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Security Group: A stateless firewall that controls traffic at the subnet level.

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NACL: A virtual firewall that controls traffic at the instance level.

Question 6

Match each AWS data compression format to its typical use case.

Accepted Answer

Snappy: Designed for high speed and efficient compression, ideal for real-time data processing.. In AWS data engineering, compression format choice depends on trade-offs between compression ratio and speed. Snappy and LZO are optimized for speed, Gzip and Bzip2 for higher compression (with Bzip2 highest), and Zstandard offers a middle ground. Common misassociations include confusing Gzip with Bzip2 for highest compression and missing Snappy's speed focus.

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Gzip: Provides the highest compression ratio, best for archival storage.

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Bzip2: Commonly used for log files due to good compression ratio.

Question 7

Match each AWS data analytics service to its primary function.

Accepted Answer

Amazon Athena: Query data in Amazon S3 using standard SQL. The correct matches are: Amazon Athena for serverless SQL querying on S3, Amazon Redshift for data warehousing, Amazon EMR for big data processing, and Amazon Kinesis for real-time streaming. Common confusions include swapping the roles of Athena and Redshift.

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Amazon Athena: Fully managed data warehouse

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Amazon Redshift: Query data in S3 using SQL

Question 8

Match each AWS Glue component to its role.

Accepted Answer

Data Catalog: Central metadata repository for storing table definitions and schema.. AWS Glue components work together for ETL. The Data Catalog stores metadata, Crawlers populate the catalog, Classifiers infer schema, and ETL Jobs execute transformations. Connections provide connectivity but are not listed here.

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Data Catalog: Executes transformation scripts.

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Crawler: Stores configuration for connecting to data stores.

Question 9

Match each AWS data migration tool to its primary function.

Accepted Answer

AWS Database Migration Service (DMS): Migrates databases to AWS with minimal downtime. AWS DMS migrates databases with minimal downtime; AWS Snowball transfers large datasets physically; AWS DataSync automates online data transfer. Common confusions include swapping tool functions or attributing schema conversion to DataSync instead of SCT.

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AWS Database Migration Service (DMS): Transfers large datasets via physical devices

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AWS Snowball: Migrates databases to AWS with minimal downtime

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AWS DataSync: Converts database schema to target platform

Question 10

Match each AWS monitoring tool to its primary use.

Accepted Answer

CloudWatch: Monitor metrics, logs, and alarms. CloudWatch monitors metrics and logs, CloudTrail audits API calls, X-Ray traces requests, and Trusted Advisor provides optimization recommendations. Common confusions include swapping the roles of CloudWatch and CloudTrail.

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CloudWatch: Auditing API activity

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CloudTrail: Monitor metrics, logs, and alarms