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EMC D-AA-OP-23 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Advanced Analytics Implementation | 15% | - Performance tuning and scalability - Machine learning model deployment - Distributed computing and optimization |
| Topic 2: Social Network Analysis (SNA) | 23% | - Graph databases and network visualization - Centrality, connectivity, and influence measures - Graph theory and network metrics - Community detection algorithms |
| Topic 3: Data Visualization | 12% | - Chart selection and data storytelling - Interactive dashboards and reporting - Tools for visualization implementation - Visualization principles and best practices |
| Topic 4: Hadoop Ecosystem and NoSQL | 15% | - HDFS, YARN, MapReduce architecture - Hive, Pig, Spark processing frameworks - NoSQL databases: Cassandra, MongoDB - Data models and scalable storage solutions |
| Topic 5: Data Science Theory and Methods | 15% | - Ethics and data governance - Model evaluation and validation metrics - Regression, classification, clustering algorithms - Statistical inference and hypothesis testing |
| Topic 6: Natural Language Processing (NLP) | 20% | - Sentiment analysis and topic modeling - NLP pipelines and applications - Named entity recognition - Text preprocessing and feature extraction |
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