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EMC D-DS-OP-23 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Processing Frameworks | 22% | - Hadoop ecosystem tuning - Apache Spark optimization - Batch and real-time processing optimization |
| Storage & Data Management | 18% | - Distributed storage system optimization - SQL/NoSQL performance tuning - Data formats, partitioning, and indexing |
| Streaming & IoT Data Processing | 15% | - Real-time ingestion frameworks - Stream processing optimization - Pravega, Kafka, NiFi usage |
| Monitoring, Troubleshooting & Workload Management | 10% | - Cluster resource allocation - Performance monitoring and logging - Bottleneck identification and resolution |
| Governance, Security & Compliance | 15% | - Regulatory compliance - Data governance policies - Security and privacy protection |
| Data Pipeline Optimization | 20% | - ETL/ELT workflow optimization - Reduce latency and improve throughput - Design scalable and efficient data pipelines |
EMC Dell Data Scientist and Data Engineering Optimize 2023 Sample Questions:
1. What ordered set of terms refers to the process in which data is sourced from a relational database, enriched and merged with other datasets, then stored in a data lake?
A) Atomicity, Consistency, and Isolation
B) Extract, Load, and Transform
C) Isolation, Atomicity, and Consistency
D) Extract, Transform, and Load
2. A manufacturing organization intents to minimize production costs by analyzing real-time data after implementing IoT tools.
Which business driver would be affected if the organization follows this strategy?
A) New sources of revenue
B) Product choices
C) Operational efficiency
D) Customer experience
3. What enables Apache Spark to process data more efficiently than Hadoop's MapReduce?
A) Apache Flink is the compute engine
B) Intermediate processing data is always written to disk
C) JobTracker functionality has been replaced by YARN
D) Data is cached in memory whenever possible
4. What is a significant advantage of using a columnar store NoSQL database for analytical workloads?
A) High-speed transaction processing
B) Real-time data synchronization
C) Efficient storage of hierarchical data
D) Optimized query performance on large datasets
5. With Apache Kafka, what is an advantage of implementing the Publish/Subscribe messaging system over Point-to-Point messaging system?
A) Any message published to a topic is immediately received by all the subscribers to that topic
B) Any message published to a topic is received only by a few subscribers to that topic
C) Messages stored are deduplicated automatically to increase the overall storage capacity of a topic
D) Messages can be dynamically moved between topics to improve the overall throughput of the system
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: A |






