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GAQM CBDFS-001 dumps - in .pdf

CBDFS-001 pdf
  • Exam Code: CBDFS-001
  • Exam Name: Certified Big Data Foundation Specialist (CBDFS)
  • Updated: Sep 17, 2026
  • Q & A: 0 Questions and Answers
  • Convenient, easy to study.
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  • Exam Code: CBDFS-001
  • Exam Name: Certified Big Data Foundation Specialist (CBDFS)
  • Updated: Sep 17, 2026
  • Q & A: 0 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine

GAQM CBDFS-001 dumps - Testing Engine

CBDFS-001 Testing Engine
  • Exam Code: CBDFS-001
  • Exam Name: Certified Big Data Foundation Specialist (CBDFS)
  • Updated: Sep 17, 2026
  • Q & A: 0 Questions and Answers
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GAQM CBDFS-001 Exam Syllabus Topics:

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

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