Real EMC D-DS-OP-23 practice exam questions for easy pass!
Last Updated: Aug 07, 2026
No. of Questions: 103 Questions & Answers with Testing Engine
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Pipeline Optimization | 20% | - ETL/ELT workflow optimization - Reduce latency and improve throughput - Design scalable and efficient data pipelines |
| Topic 2: Data Processing Frameworks | 22% | - Apache Spark optimization - Hadoop ecosystem tuning - Batch and real-time processing optimization |
| Topic 3: Monitoring, Troubleshooting & Workload Management | 10% | - Cluster resource allocation - Performance monitoring and logging - Bottleneck identification and resolution |
| Topic 4: Streaming & IoT Data Processing | 15% | - Pravega, Kafka, NiFi usage - Real-time ingestion frameworks - Stream processing optimization |
| Topic 5: Governance, Security & Compliance | 15% | - Security and privacy protection - Data governance policies - Regulatory compliance |
| Topic 6: Storage & Data Management | 18% | - Data formats, partitioning, and indexing - SQL/NoSQL performance tuning - Distributed storage system optimization |
1. What is the purpose of memory management in Apache Flink?
A) Convert all of the data into Java objects
B) Control how much memory the runtime operations use
C) Ensure no disk space is ever required
D) Eliminate the need for serialization of the data
2. Which of the following are characteristics of the Hadoop ecosystem? (Select all that apply)
A) Low fault tolerance
B) Single-node architecture
C) Scalability
D) Batch processing
E) Real-time processing
3. What is a common use case for a document-based NoSQL database like MongoDB?
A) Storing structured tabular data
B) Tracking real-time data streams
C) Performing complex SQL queries
D) Managing hierarchical data
4. Which of the following are components of the Apache Spark Streaming architecture? (Select all that apply)
A) Driver node
B) Worker node
C) Discretized streams (DStreams)
D) HDFS storage
E) Kafka topics
5. What is the primary advantage of using dictionaries in Python data pipelines?
A) Dictionaries allow duplicate values
B) Dictionaries support mathematical operations
C) Dictionaries offer O(1) lookup time
D) Dictionaries maintain element order
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C,D | Question # 3 Answer: D | Question # 4 Answer: A,B,C | Question # 5 Answer: C |
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