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GAQM CBDFS-001 Exam Syllabus Topics:

SectionObjectives
Big Data Analytics and Applications- Use cases
  • 1. Business intelligence applications
    • 2. Real-time analytics use cases
      - Analytical techniques
      • 1. Basic machine learning concepts
        • 2. Descriptive and predictive analytics
          Big Data Storage Technologies- NoSQL databases
          • 1. Document, column-family, and graph databases
            • 2. Key-value stores
              - Distributed storage systems
              • 1. Data replication and fault tolerance
                • 2. HDFS fundamentals
                  Security and Cloud in Big Data- Cloud platforms
                  • 1. Scalability and distributed computing in cloud
                    • 2. Cloud-based big data services overview
                      - Data security
                      • 1. Access control and encryption basics
                        • 2. Data privacy considerations
                          Data Management and Governance- Data integration
                          • 1. Data pipelines and ingestion methods
                            • 2. ETL processes
                              - Data governance and quality
                              • 1. Metadata and data cataloging
                                • 2. Data quality management
                                  Big Data Processing Frameworks- In-memory and stream processing
                                  • 1. Stream processing concepts (e.g., Kafka overview)
                                    • 2. Apache Spark basics
                                      - Batch processing
                                      • 1. Distributed computation models
                                        • 2. MapReduce concepts
                                          Big Data Fundamentals- Big Data architecture overview
                                          • 1. Data pipelines and data lifecycle
                                            • 2. Batch vs streaming processing
                                              - Introduction to Big Data concepts
                                              • 1. Characteristics of Big Data (Volume, Velocity, Variety, Veracity)
                                                • 2. Traditional data vs Big Data systems

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