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EMC D-DS-OP-23 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Storage & Data Management | 18% | - SQL/NoSQL performance tuning - Data formats, partitioning, and indexing - Distributed storage system optimization |
| Topic 2: Data Processing Frameworks | 22% | - Batch and real-time processing optimization - Hadoop ecosystem tuning - Apache Spark optimization |
| Topic 3: Data Pipeline Optimization | 20% | - ETL/ELT workflow optimization - Design scalable and efficient data pipelines - Reduce latency and improve throughput |
| Topic 4: Monitoring, Troubleshooting & Workload Management | 10% | - Performance monitoring and logging - Cluster resource allocation - Bottleneck identification and resolution |
| Topic 5: Streaming & IoT Data Processing | 15% | - Pravega, Kafka, NiFi usage - Real-time ingestion frameworks - Stream processing optimization |
| Topic 6: Governance, Security & Compliance | 15% | - Data governance policies - Security and privacy protection - Regulatory compliance |
EMC Dell Data Scientist and Data Engineering Optimize 2023 Sample Questions:
1. Refer to the exhibit.
Which shows a table named Student.
What changes must be made to the table in order to achieve 1NF?
A) Split table into two tables named Student and Zip
B) Remove duplicate rows in the table
C) Make Zip the primary key in the table
D) Split table into two tables named Student and DoB
2. Which Python library formats data into dataframes?
A) scikit-learn
B) NLTK
C) NumPy
D) Pandas
3. Which NoSQL database type is best suited for handling graph-based data structures and complex relationships?
A) Document store
B) Graph database
C) Column-family store
D) Key-value store
4. Which phase of a data analytics project involves data engineers extracting, transforming, and loading data from various sources into a centralized repository?
A) Data ingestion
B) Data exploration
C) Data visualization
D) Data modeling
5. In a data analytics project, what is the primary responsibility of a data engineer?
A) Building data pipelines and ETL processes
B) Conducting statistical analysis
C) Creating data visualizations
D) Designing machine learning models
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: A |
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