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EMC D-DS-OP-23 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Processing Frameworks | 22% | - Apache Spark optimization - Batch and real-time processing optimization - Hadoop ecosystem tuning |
| Streaming & IoT Data Processing | 15% | - Real-time ingestion frameworks - Pravega, Kafka, NiFi usage - Stream processing optimization |
| Data Pipeline Optimization | 20% | - Design scalable and efficient data pipelines - ETL/ELT workflow optimization - Reduce latency and improve throughput |
| Monitoring, Troubleshooting & Workload Management | 10% | - Cluster resource allocation - Bottleneck identification and resolution - Performance monitoring and logging |
| Governance, Security & Compliance | 15% | - Regulatory compliance - Security and privacy protection - Data governance policies |
| Storage & Data Management | 18% | - SQL/NoSQL performance tuning - Data formats, partitioning, and indexing - Distributed storage system optimization |
EMC Dell Data Scientist and Data Engineering Optimize 2023 Sample Questions:
1. What is the primary purpose of Apache Kafka in a data processing architecture?
A) Running complex SQL queries
B) Processing real-time data streams
C) Running machine learning algorithms
D) Storing historical data
2. Match each Apache Kafka component with its description.
3. Which component of the Apache Atlas framework allows metadata to be added to the Atlas environment?
A) Metadata Sources
B) Ingest/Export
C) Apps
D) Graph Engine
4. What is an advantage of avoiding bias from the data?
A) Minimize transparency at the point of data collection
B) Decrease trust between humans and machines
C) Reduce misuse of data and facilitate its transparency
D) Minimize Bias-Variance trade-off
5. In Python, which data type is one dimensional and immutable?
A) Array
B) Set
C) Tuple
D) List
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: Only visible for members | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: C |
